OUR MISSION

At Redwood, we empower our customers with lights-out automation for their mission-critical business processes.

ABOUT US

Redwood Software is the leader in full stack automation fabric solutions for mission-critical business processes. With the first SaaS-based composable automation platform specifically built for ERP, we believe in the transformative power of automation. Our unparalleled solutions empower you to orchestrate, manage and monitor your workflows across any application, service or server — in the cloud or on premises — with confidence and control. 

Redwood’s global team of automation experts and customer success engineers provide solutions and world-class support designed to give you the freedom and time to imagine and define your future. Get out of the weeds and see the forest, with Redwood Software.

CORE VALUES

One Team. One Redwood

Make Your Own Weather

Obsess over Customer Success

Work the Problem

Be Curious

Own the Outcome

Respect Each Other

YOUR IMPACT

As a Senior Solutions Engineer – Existing Accounts, you will serve as the primary technical and strategic partner for Redwood’s existing customers. This role merges the technical solutioning and expansion focus with the post-sales adoption and advocacy expertise. 

You will ensure customers realize maximum value from their Redwood investments by driving adoption, uncovering new opportunities for expansion, and acting as a trusted advisor who bridges business objectives with technical outcomes. 

You’ll partner closely with Sales, Product Management, Product Marketing, Customer Support and Engineering to drive growth, mitigate risk, and deliver measurable business value across your assigned accounts.

Customer Success & Adoption 

• Build and maintain strong, trusted relationships with technical and executive stakeholders within customer organizations. 
• Lead Health Checks, Use Case Workshops, and Business Reviews to ensure customer success and solution alignment. 
• Proactively identify adoption gaps, risk areas, and create “get-well” plans to ensure continued success and retention.
• Deeply understand each customer’s architecture, workflows, and business objectives to align Redwood capabilities with desired outcomes.
• Serve as a single point of contact for strategic and technical requirements, ensuring responsive, value-driven engagement. 

Account Expansion & Solutioning

• Collaborate with Account Executives to identify and pursue expansion opportunities within existing customers.
• Prepare and deliver high-impact product demonstrations and technical presentations tailored to customer goals.
• Guide customers through evaluations and proofs-of-concept that validate new use cases and demonstrate business value.
• Translate business challenges into technical solutions using Redwood’s automation platform.
• Develop and execute account growth strategies that align customer roadmaps with Redwood’s value proposition. 

Technical leadership & Project Management

• Act as the technical liaison and escalation point for your accounts, ensuring prompt and effective resolution of issues.
• Coordinate cross-functional teams—including Product Management, Engineering, and Professional Services—to drive successful outcomes.
• Manage concurrent projects, balancing customer priorities and internal resources to deliver on time and with excellence.
• Troubleshoot technical issues at a high level to determine the appropriate path to resolution.

Customer Advocacy & Continuous Improvement 

• Serve as the voice of the customer, providing structured feedback to internal teams to influence product direction and improve service delivery.
• Document and share best practices for implementing and optimizing Redwood solutions.
• Contribute to internal knowledge bases and process improvements that enhance team scalability and customer experience.

YOUR EXPERIENCE

• Minimum 3–5 years in a customer-facing technical role (e.g., Solutions Engineering, Technical Account Management, Technical Consulting, or Customer Success Engineering).
• Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent professional experience.
• Hands-on technical experience in enterprise software and technologies (e.g., Cloud Infrastructure, ERP, Databases, ETL, MFT, Programming, Networking, Windows, Linux, Troubleshooting).
• Ability to troubleshoot technical issues at a high level.
• High-level understanding of organizational structures in large enterprises and their typical challenges.
• High-level understanding of all aspects of ERP solutions (Financials, Procure to Pay, etc.).
• Experience with SAP ERP solutions is preferred.
• Experience with Java, SAP ABAP, SQL Developer, or similar is preferred.
• Experience with LLMs and AI solutions is preferred.
• Ability to quickly learn, articulate, and demonstrate complex solutions.
• Exceptional written, verbal, and presentation skills for technical and executive audiences.
• Strong organizational skills, capable of managing multiple high-impact initiatives simultaneously.
• Analytical and structured approach to problem-solving and process improvement.
• Willingness to travel approximately 20–40%, depending on customer and business needs.

We are seeking a skilled Middle AI Engineer with a deep understanding of the latest trends to join our international team. As a mid-level contributor, you will design and implement agentic AI solutions that enhance automation, decision-making, and system intelligence across the enterprise. This role is ideal for developers with hands-on experience in AI/ML, LLMs, and autonomous agents, and a passion for building scalable, intelligent systems that drive operational excellence.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client  

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design, develop, and deploy AI-driven applications and agentic systems using LLMs, transformers, and reinforcement learning
• Build intelligent automation pipelines for tasks such as incident triage, anomaly detection, and operational decision support
• Collaborate with SRE, DevOps, and product teams to integrate AI capabilities into existing infrastructure and workflows
• Develop and fine-tune models for natural language understanding, system behavior prediction, and autonomous task execution
• Implement scalable APIs and microservices for AI model serving and orchestration.
• Apply prompt engineering and retrieval-augmented generation (RAG) techniques to improve model performance and contextual accuracy
• Contribute to architectural decisions, model evaluation strategies, and continuous learning systems
• Align with team schedules (daily meetings and reviews between 3–7 PM CET)

What You Bring

• Experience in AI/ML development, software engineering, or related roles
• Proficiency in Python and frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers
• Experience with LLMs (e.g., OpenAI, Anthropic, Mistral) and agentic frameworks (e.g., LangChain, AutoGPT, CrewAI)
• Understanding of machine learning, deep learning, and reinforcement learning principles
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes)
• Experience with MLOps tools and practices for model deployment
• Knowledge of observability and telemetry systems for AI performance tracking
• Excellent problem-solving skills, communication, and a collaborative mindset

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Your Opportunity

At New Relic, we provide our customers real-time insights so they can innovate faster. Our  software delivers insightful observability tools across different technologies and distributed systems, enabling software engineering teams to quickly identify, understand and solve issues, analyze performance and get the most of their software and infrastructure.

If you love scale and want to contribute to one of the largest and fastest growing big data platforms in the world we’d love to hear from you: New Relic is looking for a passionate software engineer to join one of our core data teams in Hyderabad and work on the high-performance, big data components that power New Relic's world-class suite of software analytics products.

You will be at the heart of New Relic’s engineering process and will be building, extending, and supporting a core set of services which all of New Relic’s agents connect to every hour of every day processing millions of messages per second, handling petabytes of data as part of a distributed team that values both collaboration and individual focus to solve challenging engineering problems.

What You’ll Do

• Architect & Execute: Lead the design of end-to-end features, from high-performance React-based interfaces to scalable Java/Python microservices.
• AI Innovation: Drive the integration of LLMs and AI agents into the New Relic ecosystem, including building and maintaining MCP (Model Context Protocol) servers to bridge our data with AI models.
• Scale Heavily: Build and maintain highly available, multi-threaded backend services that handle massive data throughput and concurrency.
• Technical Leadership: Act as a force multiplier. You’ll lead system architecture discussions, conduct deep-dive code reviews, and set the standard for engineering excellence.
• Collaborate: Partner closely with Product and Design to translate complex data visualizations into intuitive, performant user experiences.
• Mentor: Foster a culture of growth by guiding junior and senior engineers through complex technical hurdles.

Must-haves

• Experience: 8+ years of professional software development experience, with a proven track record in a Lead or Staff capacity.
• Frontend Mastery: Deep expertise in React (preferred) or Angular, with a focus on state management, performance optimization, and data visualization.
• Backend Depth: Expert-level knowledge of Java or Python. You should be comfortable with multi-threading, concurrency patterns, and asynchronous programming.
• Distributed Systems: Extensive experience designing and scaling distributed architectures that operate under high load.
• AI/ML Familiarity: Experience working with LLM APIs, prompt engineering, or building MCP servers to enable AI-driven workflows.
• Leadership: Experience leading cross-functional projects and mentoring mid-to-senior level engineers.

Nice-to-haves

• Experience with Front End technologies (HTML, Javascript, CSS, Angular, React)
• Experience with Go or other high-concurrency languages.
• Knowledge of Big Data technologies (Kafka, ClickHouse, or Spark).
• Familiarity with Kubernetes, Docker, and modern CI/CD pipelines.
• Contributions to open-source projects or the AI/MCP community.

THE ROLE

Join the Infrastructure and Shared Services (ISS) team as a Security Engineer to build and defend the next generation of the Everpure Platform. Whether your expertise lies in network architecture, detection engineering, or securing AI pipelines, you will play a critical role in protecting our engineering infrastructure from lateral movement and advanced threats. You’ll collaborate directly with Platform Reliability and Infrastructure teams to bake security into the automation that powers our global developer services. This is a high-impact, hands-on engineering role focused on creating a resilient, zero-trust environment for our most critical services.

WHAT YOU'LL DO

• Engineer Advanced Defense Patterns: Design and implement zero-trust network access models, secure service-to-service communication, or AI-specific guardrails to eliminate unauthorized data access and lateral movement.
• Operationalize Detection & Response: Build high-fidelity behavioral detections for infrastructure and identity systems, ensuring all security telemetry is integrated into our SIEM for real-time visibility and rapid incident containment.
• Validate & Harden Infrastructure: Conduct threat modeling and security validation exercises (including ransomware simulations) to verify the effectiveness of controls across Kubernetes, cloud-native workloads, and AI model pipelines.
• Automate Security at Scale: Partner with engineering teams to integrate security controls directly into infrastructure-as-code and CI/CD pipelines, automating log analysis and network policy enforcement to reduce manual overhead.

WHAT YOU BRING

• Advanced knowledge of securing distributed systems, with deep technical proficiency in either network protocols (TCP/IP, TLS/SSL), detection engineering methodologies, or AI/ML pipeline security (protecting against prompt injection and data leakage).
• Hands-on experience securing cloud-native environments (AWS/Azure/GCP), containerized workloads (Kubernetes), and modern infrastructure-as-code automation.
• Ability to distinguish legitimate operational activities from indicators of compromise through deep log analysis, packet inspection (Wireshark), or behavioral modeling in SIEM/XDR platforms.
• Proven track record of working alongside DevOps, SOC, and Data teams to drive security outcomes without compromising engineering velocity.
• We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Everpure’s policies, unless you are on PTO, or work travel, or other approved leave.

  #LI-ONSITE

The Team

We are seeking an experienced System Engineer to join our End User Engineering team. You’ll play a critical role in building and maintaining the automation frameworks that underpin our End User infrastructure operations. This position offers the opportunity to work with cutting-edge technologies at scale, supporting our End User platforms.

You should have the enthusiasm for leveraging AI development tools to accelerate delivery and driving their adoption across the team.

Role Responsibilities

As an System Engineer, you’ll design, implement, and maintain infrastructure-as-code solutions, configuration management, monitoring systems, whilst also supporting business-as-usual activities.

You’ll work closely with the entirety of our infrastructure organization, and other platform teams to drive automation initiatives that help us further provide platforms that drive our delivery. The role is subject to on-call rotation.

Key Competencies

Required

• Experience supporting End User platforms such as Microsoft 365 and Slack.
• Exposure to identity management and associated technologies (Active Directory, Entra ID).
• Experience supporting End User clients such as Windows, MacOS, and mobile devices.
• Proficiency with automation tools (Ansible, Terraform) and scripting/programming languages (Python, Go, PowerShell).
• Strong troubleshooting and debugging skills across distributed systems, with the ability to diagnose complex production issues under pressure.
• Awareness of security best practices, and infrastructure architecture patterns.
• Embracing agentic engineering — willingness and ability to work effectively with AI -assisted development tools as part of daily workflow

Advantageous

• Experience with device management, including Intune and Jamf
• Hands-on experience with observability and monitoring tools (Prometheus, Grafana, ELK, Loki, or similar).
• Experience with CI/CD pipelines and source control workflows (Git, Jenkins, TeamCity).
• Knowledge of AI/LLM concepts (context windows, prompt tuning, MCP servers).
• Self-organised with the ability to prioritise and effectively manage time across multiple projects. 
• Excellent communication and problem-solving skills with the ability to explain complex technical concepts to diverse audiences.  

Benefits

• Modern office located in the OfficeX campus with easy access to transport and amenities.
• Hybrid working model
• Competitive compensation package
• 25 days holiday allowance
• Premium Health insurance
• Employee Assistance program
• Referral Bonus
• Additional days off for long service and volunteering
• Multisport card
• Opportunities for professional development including internal tech talks
• Conference attendance, and engagement with the open-source community.

So, what’s the role all about?

As AI Quality Architect, you are the person who makes quality native to the agentic SDLC. You design the systems, standards, and intelligence layers that ensure every stage of an AI-accelerated pipeline — from requirement ingestion to autonomous deployment — is observable, trustworthy, and continuously improving. You don't retrofit testing onto AI workflows; you architect quality into them from the ground up.

How will you make an impact?  

Agentic Quality Architecture

• Design the end-to-end quality architecture for agentic SDLC pipelines — spanning requirement analysis, code generation, test creation, execution, triage, and release gates
• Define how quality agents are orchestrated: which decisions they own autonomously, which require human-in-the-loop checkpoints, and how confidence thresholds govern both
• Architect multi-agent quality workflows: requirement validation agents, test generation agents, failure triage agents, and regression analysis agents working in coordinated pipelines
• Establish trust and verification models for agent-produced artifacts — test code, assertions, coverage reports, and defect analyses must all be auditable and traceable
• Own the architectural patterns for quality feedback loops between agents: how a deployment agent learns from a triage agent's findings, and how that signal improves future generation

AI-Native Test Engineering Platform

• Design and own the LLM-powered test generation platform — from natural language requirement ingestion to executable, maintainable test output
• Architect the evaluation harness that continuously measures test generation quality: coverage delta, false-positive rates, assertion accuracy, and maintenance burden over time
• Build the self-healing test infrastructure layer — agents that detect broken selectors, drifted APIs, or changed behaviors and propose or apply fixes autonomously
• Define the prompt engineering standards, context injection patterns, and RAG architectures that ground test generation agents in real codebase context
• Architect test artifact governance: versioning, ownership attribution (human vs. agent), rollback capability, and confidence scoring for every generated artifact

Quality Gates in Autonomous Pipelines

• Design intelligent, adaptive quality gates that operate at the speed of agentic CI/CD — gates that reason about risk, not just pass/fail thresholds
• Build risk-scoring models that dynamically adjust gate strictness based on change scope, code origin (human vs. AI-generated), historical failure patterns, and deployment context
• Architect the observability layer for agentic pipelines: what signals indicate a pipeline agent is making poor quality decisions, and how are those signals surfaced in real time
• Define the integration patterns between quality gates and orchestration platforms (LangChain, LlamaIndex, custom agent frameworks) used across the engineering org
• Establish rollback and circuit-breaker patterns for autonomous deployments triggered by quality signal degradation

AI Model & Agent Validation

• Build behavioral testing frameworks for validating AI agents and LLM-powered features in production — testing non-deterministic outputs with statistical rigor
• Design evaluation benchmarks for internal AI tooling: measuring agent task completion accuracy, hallucination rates, context retention, and decision quality over time
• Architect drift detection systems that identify when agent behavior changes between model versions, prompt updates, or context window shifts
• Define adversarial and edge-case testing methodologies for AI features: prompt injection resistance, boundary condition handling, and graceful degradation under distribution shift
• Partner with ML platform and data science teams to establish quality acceptance criteria for every model and agent promoted to production

Have you got what it takes?

• 12+ years in software engineering with strong depth across both development and quality engineering
• 4+ years as a hands-on principal architect or distinguished engineer with cross-org technical scope
• Demonstrated experience designing quality infrastructure used at scale — 50+ engineers, high-velocity pipelines, enterprise SLAs
• Direct production experience building or operating systems that incorporate LLMs or AI agents — not evaluations, but shipped systems
• Background in large-scale CI/CD architecture and the performance engineering domain
• Enterprise SaaS or platform engineering background; familiarity with regulated, high-uptime environments strongly preferred

Agentic AI & LLM Proficiency

• Deep, hands-on understanding of agentic AI patterns: tool use, multi-agent orchestration, planning loops, memory architectures, and human-in-the-loop design
• Expert-level prompt engineering including chain-of-thought, few-shot, RAG, and structured output techniques applied to code and test generation
• Experience designing evaluation harnesses for non-deterministic AI systems — statistical confidence, behavioral consistency, and regression detection
• Familiarity with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or equivalents) and their tradeoffs in production quality pipelines

Technical Depth

• Expert in Python and TypeScript; proficient in at least one compiled language (Java, Go, C#)

• Strong CI/CD architecture skills: Jenkins, GitHub Actions, pipeline-as-code, artifact management

Leadership & Influence

• Proven ability to drive technical consensus and architectural adoption across multiple teams without direct authority
• Exceptional written communication — your ADRs, RFCs, and design docs set the standard others follow
• Effective technical mentor to senior and staff engineers; you expand the thinking of those around you
• Comfortable and credible presenting to VP and C-level stakeholders; you make complex architecture legible to executives

What’s in it for you?

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10833
Reporting into: Senior Director, Engineering, CX
Role Type: Individual Contributor

#LI-Hybrid

Role Description

• As a Senior Management & Technology Consultant - AI & Process Analytics (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Consultant (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Architect (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Engineer, you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Consultant (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Management & Technology Consultant - AI & Process Analytics (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Architect (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Engineer, you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Strategic Value & Process Optimisation Consultant (Internal Title: Senior Value Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Management & Technology Consultant – AI & Process Analytics (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Strategic Value & Process Optimisation Consultant (Internal Title: Senior Value Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Management & Technology Consultant – AI & Process Analytics (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Consultant (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Consultant (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Architect (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

Role Description

• As a Senior Applied AI Solutions Architect (Internal Title: Senior Applied AI Engineer), you will work directly with our most strategic customers to understand their objectives and key challenges, identify high-impact opportunities for AI, and turn them into measurable business value. You will be building Celonis solutions using the world’s leading Process Intelligence (PI) platform - in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

This customer-facing role is ideal for people who enjoy working directly with customers and turning complex business challenges into practical AI solutions. The focus is on problem framing, solution design, and business impact rather than pure software engineering. While you will prototype AI solutions, the primary goal is delivering meaningful value for customers.

Key Responsibilities:

• Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
• Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
• Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
• Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
• Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.
• Develop Domain Expertise: Build deep expertise in specific industries or business domains (e.g., supply chain, finance) and help scale that knowledge across the organization.

You might be a great fit if you...

• have 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
• enjoy translating business challenges into technical solutions
• can communicate complex technical concepts to business and executive stakeholders
• have a good understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• demonstrate strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• have some experience prototyping solutions with Python and modern AI frameworks
• are familiar with Generative AI architectures such as RAG, prompt engineering, or agent-based systems
• hold a Bachelor’s Degree required (Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience is a nice-to-have).

Nice to have (big plus):

• Experience building or deploying generative AI applications
• Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
• Industry experience in domains such as supply chain, finance, or operations

The GenAI Security team within Reddit’s Security, Privacy, Assurance, and Corporate Engineering organization protects Reddit’s GenAI usage across employee tools, internal agents, and production user-facing systems. Our mission is to secure and protect Reddit’s AI traffic and GenAI adoption by default.

We are building zero-trust, defense-in-depth systems that verify identity, permissions, data access, and semantic intent across AI workflows. A core part of this work is developing practical, high-quality ML models that detect and prevent security risks such as prompt injection, jailbreak attempts, sensitive data exfiltration, unsafe model behavior, anomalous usage, and unauthorized agent actions.

We are looking for a Senior Machine Learning Engineer to lead model development for GenAI Security and help establish strong ML practices across SPACE. This role owns the full machine learning lifecycle: problem definition, data ETL, feature engineering, model training, model evaluation, deployment, experimentation, prediction, monitoring, debugging, and retraining.

What You’ll Do

• Build and improve security-focused ML models for Reddit’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection models, and other neural network based security signals.
• Own model development end to end: define the security problem, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain from production feedback.
• Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where they are the right practical fit.
• Design rigorous evaluation suites for adversarial examples, hard negatives, long-context inputs, structured payloads, tool calls, multi-turn workflows, and real production traffic.
• Improve model precision, recall, latency, cost, calibration, and operational reliability for high-impact production surfaces.
• Build repeatable MLOps workflows for SPACE, including training pipelines, model lineage, artifact management, holdout evaluation, dashboards, rollback paths, and retraining loops.
• Partner closely with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to bring security models into real production workflows.
• Work pragmatically with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed to keep model iteration moving.
• Translate security goals into measurable model outcomes and help partners understand tradeoffs between risk reduction, latency, false positives, and product impact.
• Provide technical direction to other engineers and serve as a go-to ML expert for GenAI Security and broader SPACE model needs.

Who You Might Be

• 5+ years of experience building, training, evaluating, and deploying production ML or deep learning models.
• Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, or similar.
• Strong practical understanding of the full ML lifecycle: problem definition, data ETL, feature engineering, training, evaluation, deployment, monitoring, debugging, and retraining.
• Experience building data pipelines and working with large-scale datasets.
• Experience designing rigorous model evaluations, including precision/recall/F1, false positive analysis, threshold tuning, calibration, holdout sets, regression tests, and production-quality validation.
• Experience shipping production-quality software, preferably in Python and/or Go.
• Strong communication skills and ability to explain model behavior, risk tradeoffs, and technical decisions to cross-functional partners.
• BS degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
• Experience in the following areas is a plus:
  • Applying ML to security, privacy, trust and safety, abuse prevention, adversarial ML, or GenAI security problems.
  • Training or fine-tuning neural text models for complex inputs such as long-context prompts, structured payloads, code-like content, multi-turn interactions, or tool calls.
  • Production MLOps or model serving systems such as Airflow, Ray, MLflow, Triton, ONNX, Kubernetes, or similar.
  • Improving model quality through labeling strategy, hard-negative mining, synthetic data generation, distillation, or active learning.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-remote

Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for:

• The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources).
• Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics.
• Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations.
• Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs.
• Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. 

We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems. Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems). 

Responsibilities:

• Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft.
• Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. 
• Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)
• Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products.
• Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure efficient, reliable serving at Reddit scale.
• Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.
• Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable, resilient MLOps pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production.

Required Qualifications:

• 7+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads. 
• Demonstrated Staff-level technical leadership: has driven architecture decisions, standards, and design reviews across multiple teams, and has aligned PMs, DSs, and engineers on shared ML systems or platforms without direct people-management authority.
• Excellent communication skills, with the ability to explain complex technical trade-offs to PMs, DSs, and other engineering teams, especially in ambiguous, cross-team problem spaces like Seekers/Searchers monetization. 
• Strong track record building and shipping NLP / Language models / content understanding models to production (e.g., classifiers, encoders, sequence or session models), with clear business outcomes (e.g., CTR/ROAS uplift, safety improvements). Experience with commercial or intent modeling is a strong plus.
• Practical experience using LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), including managing quality, cost, and latency trade-offs.
• Deep experience with PyTorch, TensorFlow, or similar, and production-quality code in Python (and ideally one statically typed language like Go/Java/C++). Comfortable owning training, evaluation, and deployment code end-to-end.
• Experience designing ML systems and pipelines: offline training, feature pipelines (batch/streaming), online serving, monitoring, and experimentation for high-traffic surfaces.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-Remote

¿Quieres cambiar el mundo? 

Eso es lo que hacemos en Cabify. Nuestro objetivo es hacer de las ciudades mejores lugares para vivir, mejorando la movilidad de las personas que viven en ellas, conectando a pasajeros y conductores con tan sólo pulsar un botón. Es posible que algún día las ciudades sean lugares donde nadie necesite un coche privado, pero aún nos queda un largo camino por recorrer… ¿nos acompañas?

Fundada en 2011, nos hemos convertido en el primer ‘unicornio’ español. Nuestra sede central está en Madrid pero actualmente nos encontramos en 38 ciudades de España y Latinoamérica. Y cada mes que pasa más gente se une a nuestro equipo internacional lleno de personas apasionadas, brillantes y con talento con ganas de desafiar el “status quo”.

Pero no importa lo rápido que crezcamos o lo grande que nos volvamos, queremos mantener nuestro espíritu ‘start-up’. Somos un equipo seguro de sí mismo, energético, profesional y carismático, y estamos orgullosos de hacer las cosas bien. Nos gusta pensar en nosotros mismos como una empresa de tecnología ética e innovadora que ha creado un negocio donde todos son tratados de manera justa y respetuosa, desde nuestros ingenieros hasta los conductores que utilizan nuestra plataforma. Además, siempre cumplimos plenamente con las regulaciones gubernamentales y respetamos las leyes locales. 

Hemos recorrido un largo camino hasta ahora, pero en realidad nuestro viaje no ha hecho más que comenzar. Si vamos a convertir nuestra misión en una realidad, ¡necesitamos que personas con talento y ambición como tú se unan a nuestro equipo!!

Sobre el puesto

Buscamos un/a analista apasionado/a por la automatización, la tecnología y la inteligencia artificial, que disfrute transformar procesos manuales y datos dispersos en soluciones inteligentes, escalables y predictivas.

Que impulse la eficiencia operativa en nuestra operación, mediante el diseño, construcción y despliegue de soluciones tecnológicas con uso de IA y automatización, logrando transformar procesos manuales en flujos inteligentes, garantizando que la operación será escalable, predictiva y esté alineada con los objetivos de Cabify. 

¿Cómo nos ayudarás a cumplir con nuestra misión?

• Implementar oportunidades de automatización y soluciones con uso de IA en procesos internos y externos que generen ahorros tangibles de tiempo y recursos de forma inmediata. 
• Desarrollar herramientas de análisis para la toma de decisiones en el área.
• Identificación y diagnóstico: Ejecutar shadowing operativo para mapear fricciones y procesos manuales en nuestra operación. Logrando propuestas e implementación de proyectos y procesos que apoyen en la mejora continua.
• Orquestación de Pipelines de Datos: Configurar y mantener conectores automatizados que unifiquen el flujo de información entre Ingeniería de Conocimiento (RAG) y herramientas de gestión (Zendesk), telefonía e infraestructura de voz (Aircall / Amazon Connect) y gestión de tareas (Jira Service Management) y reportería de datos empleando Tableau.

Funciones principales:

• Arquitectura de Agentes IA: Diseñar y desplegar agentes de IA generativa para la creación automática de contenidos, evaluaciones técnicas y rutas de aprendizaje dinámicas.
• Modelado Predictivo de Performance: Desarrollar algoritmos que identifiquen brechas de desempeño y riesgos operativos antes de que afecten los KPIs de la operación.
• Ingeniería de Conocimiento (RAG): Construir y optimizar las bases de datos y de conocimiento que alimentan a los agentes de IA, asegurando respuestas precisas y actualizadas.
• Integración E2E: Automatizar mediante flujos inteligentes (Workflows) el ciclo completo de procesos, eliminando la intervención manual en el registro y seguimiento.
• Interoperabilidad de Plataformas: Configurar conectores y pipelines de datos entre el CRM, sistemas de telefonía, LMS, Zendesk, Aircall, Amazon Conect, Tableau, Jira y herramientas de auditoría para unificar el reporting.
• Shadowing de Eficiencia: Identificar "ladrones de tiempo" (tareas manuales repetitivas) en la operación diaria para transformarlas en procesos automatizados con IA.
• MVP rápido: Desarrollar soluciones piloto de despliegue ágil que generen un ahorro en eficiencia operativa.
• Gobernanza técnica: Monitorear la estabilidad de los bots y agentes activos, ejecutando el mantenimiento correctivo y reportando incidentes técnicos.
• Vigilancia Tecnológica: Mantener una mentalidad de aprendizaje continuo para identificar, testear y documentar nuevas herramientas de IA, modelos de lenguaje (LLMs) y soluciones de automatización a la vanguardia del mercado. 
• Documentar los procesos actuales del contact center (mapeo de tareas manuales).

Lo que estamos buscando

Formación académica:

• Tecnólogo/oa o profesional recién graduado/a en Ingeniería de Sistemas, Ingeniería de Software, Data Engineer o carreras afines. Deseable contar con cursos, certificaciones o formación complementaria en inteligencia artificial, automatización de procesos.

Experiencia Mínima: Mínimo 1 año y medio de experiencia en el diseño e implementación de soluciones de automatización e inteligencia artificial, incluyendo:

• Ingeniería de Procesos & Mejora Continua: Historial comprobable en el mapeo, documentación y optimización de flujos operativos en entornos de alto volumen (Contact Center, Operaciones o Shared Services).
• Automatización de Ciclo de Vida: Experiencia implementando soluciones que impacten directamente en KPIs de eficiencia, tales como reducción de AHT (Average Handle Time), automatización de Onboarding o auditoría de calidad masiva.
• Gestión de Proyectos Transversales: Capacidad en gestión de incidencias y coordinación interdepartamental, asegurando que la solución técnica resuelva el problema de negocio.
• Arquitectura No-Code/Low-Code: Experiencia en orquestación de flujos mediante herramientas como Zapier, n8n o Power Automate. Capacidad para conectar APIs y gestionar Webhooks.
• Arquitectura Code:  Dominio en la creación, depuración y despliegue de scripts funcionales (JavaScript / Google Apps Script) en entornos de desarrollo integrados (IDEs) optimizados para IA, específicamente Cursor y Visual Studio Code, usando agentes con modelos de inteligencia artificial de Claude. 
• Dominio de IA Generativa Aplicada: No solo como usuario final, sino en el uso de Prompt Engineering técnico, configuración de agentes (parámetros como temperatura) y uso de modelos para generación de contenido o análisis de datos no estructurados.
• Gestión de Datos & Estructuras: Conocimiento sólido en el manejo de JSON, limpieza de datos y estructuración de bases en Google Sheets/Excel para que funcionen como "cerebros" de automatización. Se valorará positivamente el uso de SQL y Python para análisis avanzado.

Soft Skills

• Lógica Resolutiva y Pensamiento Algorítmico: Capacidad para desglosar problemas operativos complejos en pasos lógicos simples
• Curiosidad analítica y mentalidad exploratoria, con interés constante por entender procesos, datos y oportunidades de mejora.
• Proactividad y autonomía, para identificar problemas, proponer soluciones y llevarlas a implementación.
• Alta adaptabilidad a entornos dinámicos, tecnológicos y en evolución constante.
• Pensamiento crítico y estructurado, enfocado en la resolución efectiva de problemas.
• Orientación a resultados y mejora continua, con foco en impacto, eficiencia y escalabilidad.
• Buenas habilidades comunicativas

¿Qué ofrecemos?

Horario: Lunes a viernes de 8 am a 6 pm, modalidad híbrida. 
Tipo de contrato: Término indefinido    

Beneficios:

• Cabiflex: Bono mensual de $250.000 para redimir en diferentes comercios.
• Mediodía de cumpleaños
• Mediodía de cumpleaños hijos menores de 12 años
• Día libre por graduación de educación formal.
• Convenio de seguro exequial para familiares y mascotas. 
• Convenio de medicina domiciliaria.
• Convenio sistema de ahorros con Fincomercio
• Día de recarga: Tercer viernes de cada mes libre a excepción de abril y diciembre para que puedas descansar y "recargar pilas"

Innovate at the frontier of AI as a Senior Machine Learning Engineer at Exadel. Design intelligent systems, build clean data pipelines, and solve real-world problems—fast.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Innovate at the frontier of AI as a Senior Machine Learning Engineer at Exadel. Design intelligent systems, build clean data pipelines, and solve real-world problems—fast.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Innovate at the frontier of AI as a Senior Machine Learning Engineer at Exadel. Design intelligent systems, build clean data pipelines, and solve real-world problems—fast.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Innovate at the frontier of AI as a Senior Machine Learning Engineer at Exadel. Design intelligent systems, build clean data pipelines, and solve real-world problems—fast.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Role - Senior AI Engineer

About the Role

GHX is building an LLM-powered document understanding platform — classification, structured data extraction, and intelligent orchestration at scale. This is a broad AI engineering role where you will own the full lifecycle from problem framing through to production quality.

You will start where the highest leverage is: designing prompts that behave like specifications and building the evaluation infrastructure that tells us whether the system actually works. Over time, the scope expands into agent orchestration, system architecture, and the migration of our existing rule-based pipeline to LLM-based equivalents.

Solid software engineering experience is a pre-requisite. You will design and build production services, own architectural decisions, and write code that others maintain. AI fluency amplifies good engineering – it does not replace it.

How the Role Evolves

Core Responsibilities

Prompt Engineering

• Design classification and extraction prompts for diverse document types
• Write prompts that function as formal specifications — unambiguous and edge-case-aware
• Build and iterate few-shot, chain-of-thought, and structured output templates
• Own the prompt library, versioning, and rollback strategy

LLM Output Evaluation

• Define and curate ground truth datasets for classification and extraction tasks
• Build automated evaluation pipelines tracking precision, recall, and field-level accuracy
• Validate outputs against intent — catch what is technically correct but conceptually wrong

AI Agent Orchestration

• Design multi-agent pipelines for document processing workflows
• Integrate MCP servers and tool-use patterns for external service access

Software Engineering

• Build production-grade APIs and services around LLM capabilities
• Apply Clean Architecture or equivalent — design for testability and maintainability
• Write well-structured Python; own technical debt decisions consciously
• Contribute to CI/CD, observability, and deployment pipelines

Stakeholder Interface

• Serve as technical contact between business teams and the AI engineering layer
• Communicate system constraints in product language; translate product needs into system boundaries
• Surface quality metrics and model behaviour to non-technical stakeholders

Skills & Experience

Required

• Prompt engineering (advanced) & LLM evaluation frameworks
• Ground truth dataset design
• LLM APIs — OpenAI, Anthropic, Azure AI
• 8+ years overall software engineering experience preferably in Python & AWS
• AI agent orchestration
• Clean Architecture / DDD
• REST API design
• Git, CI/CD, containerisation

Nice to Have

• Document understanding / OCR tooling like Textract
• Experience working with AWS services (EC2, SQS, S3, Lambda functions, ECS)
• LangChain / LlamaIndex
• NLP / text classification

What Good Looks Like

• Prompt as specification. Treats prompts like specifications — precise, contract-like, with edge cases considered upfront rather than patched later.
• Verification instinct. Reads AI output critically. Catches the subtly wrong answer before it becomes an expensive data quality incident downstream.
• Evaluation-first mindset. Doesn't trust a prompt in production without a test suite. Builds measurement infrastructure as part of the feature, not after.
• Architectural thinking. Understands how systems should be structured before implementation begins. Knows the difference between technically correct and conceptually right.
• Pattern fluency. Knows Clean Architecture, DDD, or equivalent — not the syntax, the reasoning behind the design choices.
• Communication range. Can speak to a non-technical ops manager and a distributed system at the same level of precision.

About the role

Drive the AI-native transformation of Roku's advertising business operations, identifying high-leverage opportunities and influencing roadmap, architecture, and system design across multiple teams.

Work closely with advertising business stakeholders to identify needs, surface high-impact opportunities, and translate operational pain points into ML and agentic AI solutions.

Design and ship production ML and agentic systems end-to-end, including recommendation, personalization, ranking, forecasting, anomaly detection, and multi-agent or agent-to-agent workflows, embedded directly within product and operational systems where they drive decisions.

Apply GenAI and LLMs to deliver measurable value by building and scaling Retrieval Augmented Generation (RAG) pipelines, prompt orchestration, evaluation frameworks, and guardrails, with a focus on reliability and outcomes over hype.

Translate ambiguous business problems into production solutions, partnering with engineers, data scientists, product managers, and business teams to ground ML and AI work in real operational impact.

Build and operationalize evaluation loops covering precision and recall, calibration, drift detection, and human-in-the-loop systems, and define the dashboards and Service Level Objectives (SLO) that tie model performance to business outcomes.Start from the needs of internal engineers and business operators, bringing a creative and strategic approach to simplifying systems and introducing practical, high-impact solutions.

Provide technical leadership across the broader ML and AI surface area, raising the bar for engineering rigor, mentoring engineers, and shaping how the organization thinks about AI-native systems.

For New York Only - The estimated annual salary for this position is between $195,500 - $352,100 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.

What you'll be doing 

• Drive the AI-native transformation of Roku's advertising business operations, identifying high-leverage opportunities and influencing roadmap, architecture, and system design across multiple teams.
• Work closely with advertising business stakeholders to identify needs, surface high-impact opportunities, and translate operational pain points into ML and agentic AI solutions.
• Design and ship production ML and agentic systems end-to-end, including recommendation, personalization, ranking, forecasting, anomaly detection, and multi-agent or agent-to-agent workflows, embedded directly within product and operational systems where they drive decisions.
• Apply GenAI and LLMs to deliver measurable value by building and scaling Retrieval Augmented Generation (RAG) pipelines, prompt orchestration, evaluation frameworks, and guardrails, with a focus on reliability and outcomes over hype.
• Translate ambiguous business problems into production solutions, partnering with engineers, data scientists, product managers, and business teams to ground ML and AI work in real operational impact.
• Build and operationalize evaluation loops covering precision and recall, calibration, drift detection, and human-in-the-loop systems, and define the dashboards and Service Level Objectives (SLO) that tie model performance to business outcomes.
• Start from the needs of internal engineers and business operators, bringing a creative and strategic approach to simplifying systems and introducing practical, high-impact solutions.
• Provide technical leadership across the broader ML and AI surface area, raising the bar for engineering rigor, mentoring engineers, and shaping how the organization thinks about AI-native systems.

We're excited if you have 

• Master's or PhD in Computer Science, Mathematics, Statistics, or a related technical field, or equivalent practical experience.
• 8+ years of hands-on engineering experience, with a track record of technically leading and delivering multiple complex ML and AI initiatives.
• Strong foundation in machine learning and statistical modeling, including clustering, classification, regression, decision trees, neural networks, SVMs, and anomaly detection, with deep understanding of supervised and unsupervised learning, feature engineering, model evaluation, bias-variance tradeoffs, and offline vs. online metrics.
• Proven experience building and scaling production ML and AI systems, including LLMs, RAG architectures, embeddings, retrieval-based systems, and multi-agent or agent-based system design.
• Hands-on experience designing, training, tuning, and deploying models for ranking, prediction, recommendation, forecasting, classification, or NLP use cases.
• Demonstrated technical leadership, including setting direction, influencing across teams, and elevating the work of other engineers.
• Experience in advertising, marketplaces, e-commerce, travel, or similar data-rich, decision-driven platforms is a strong plus.

#LI-RN1

About the role

Drive the AI-native transformation of Roku's advertising business operations, identifying high-leverage opportunities and influencing roadmap, architecture, and system design across multiple teams.

Work closely with advertising business stakeholders to identify needs, surface high-impact opportunities, and translate operational pain points into ML and agentic AI solutions.

Design and ship production ML and agentic systems end-to-end, including recommendation, personalization, ranking, forecasting, anomaly detection, and multi-agent or agent-to-agent workflows, embedded directly within product and operational systems where they drive decisions.

Apply GenAI and LLMs to deliver measurable value by building and scaling Retrieval Augmented Generation (RAG) pipelines, prompt orchestration, evaluation frameworks, and guardrails, with a focus on reliability and outcomes over hype.

Translate ambiguous business problems into production solutions, partnering with engineers, data scientists, product managers, and business teams to ground ML and AI work in real operational impact.

Build and operationalize evaluation loops covering precision and recall, calibration, drift detection, and human-in-the-loop systems, and define the dashboards and Service Level Objectives (SLO) that tie model performance to business outcomes.Start from the needs of internal engineers and business operators, bringing a creative and strategic approach to simplifying systems and introducing practical, high-impact solutions.

Provide technical leadership across the broader ML and AI surface area, raising the bar for engineering rigor, mentoring engineers, and shaping how the organization thinks about AI-native systems.

For Massachusetts Only - The estimated annual salary for this position is between $178,500 - $290,500 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off. 

What you'll be doing 

• Drive the AI-native transformation of Roku's advertising business operations, identifying high-leverage opportunities and influencing roadmap, architecture, and system design across multiple teams.
• Work closely with advertising business stakeholders to identify needs, surface high-impact opportunities, and translate operational pain points into ML and agentic AI solutions.
• Design and ship production ML and agentic systems end-to-end, including recommendation, personalization, ranking, forecasting, anomaly detection, and multi-agent or agent-to-agent workflows, embedded directly within product and operational systems where they drive decisions.
• Apply GenAI and LLMs to create measurable value, building and scaling Retrieval Augmented Generation (RAG) pipelines, prompt orchestration, evaluation frameworks, and guardrails, with a focus on reliability and outcomes over hype.
• Translate ambiguous business problems into production solutions, partnering with engineers, data scientists, product managers, and business teams to ground ML and AI work in real operational impact.
• Build and operationalize evaluation loops covering precision and recall, calibration, drift detection, and human-in-the-loop systems, and define the dashboards and Service Level Objectives (SLO) that tie model performance to business outcomes.
• Start from the needs of internal engineers and business operators, bringing a creative and strategic approach to simplifying systems and introducing practical, high-impact solutions.
• Provide technical leadership across the broader ML and AI surface area, raising the bar for engineering rigor, mentoring engineers, and shaping how the organization thinks about AI-native systems.

We're excited if you have 

• Master's or PhD in Computer Science, Mathematics, Statistics, or a related technical field, or equivalent practical experience.
• 8+ years of hands-on engineering experience, with a track record of technically leading and delivering multiple complex ML and AI initiatives.
• Strong foundation in machine learning and statistical modeling, including clustering, classification, regression, decision trees, neural networks, SVMs, and anomaly detection, with deep understanding of supervised and unsupervised learning, feature engineering, model evaluation, bias-variance tradeoffs, and offline vs. online metrics.
• Proven experience building and scaling production ML and AI systems, including LLMs, RAG architectures, embeddings, retrieval-based systems, and multi-agent or agent-based system design.
• Hands-on experience designing, training, tuning, and deploying models for ranking, prediction, recommendation, forecasting, classification, or NLP use cases.
• Demonstrated technical leadership, including setting direction, influencing across teams, and elevating the work of other engineers.
• Experience in advertising, marketplaces, e-commerce, travel, or similar data-rich, decision-driven platforms is a strong plus.

#LI-RN1

About The Role

As a Senior Software Engineer, Android on the Roku Mobile App team, you will help shape the future of how millions of users interact with their Roku Streaming Devices. You’ll work on building intuitive, reliable, and highly performant Android experiences that allow customers to monitor and control Roku streaming devices from TVs to Players and beyond.

This role offers the opportunity to work across a modern, evolving tech stack including Kotlin, Compose, and Googles’s latest frameworks. You’ll collaborate closely with design, product, and cross-functional engineering teams to bring innovative features to life, improve performance, and make every day smart home interactions seamless.

You should be motivated by curiosity and initiative, eager to take ownership of features and run with them, while remaining grounded in a team-first, collaborative mindset.

About The Team

You will be joining a talented, high-performance team with a history of delivery. We are looking for someone who can help us keep up this pace and continue delivering high-quality app as we grow.

With so many people using our products globally, we’ve become well-known for products that “just work” right out of the box and integrate almost by magic. That doesn’t happen by accident, which is why we are committed to making sure our products aren’t just intuitive, they’re obvious

What You’ll Be Doing

• Design and build advanced applications and features for the Android platform
• Integrate with cloud APIs and local device communication protocols to control smart devices
• Write and maintain tests using frameworks such as JUnit and Espresso
• Collaborate with cross-functional teams to define, design, and ship new features for mobile devices, optimizing for touch experiences. Write well-designed, testable, and efficient code
• Debug, profile, and optimize app performance across a range of Android devices
• Participate in design and code reviews, helping elevate code quality across the team
• Stay up to date with Android platform capabilities, tools, and libraries, and propose how we can leverage them
• Contribute to roadmap planning, technical design, and release delivery

We’re Excited If You Have

• Professional Android development experience, ideally with Kotlin and/or Compose
• Strong experience shipping and maintaining production apps in the Play Store
• Proficiency in using AI tools (e.g., GitHub Copilot, ChatGPT) and experience with prompt engineering
• Experience working with IoT or networked device interactions is a big plus
• Familiarity with BLE, webs sockets, or MQTT protocols is a bonus
• Experience collaborating with cross-functional teams in agile environments
• Proficient in the Android development toolset
• Strong understanding of Android architecture, UI/UX patterns, and app lifecycle
• Excellent communication and debugging skills
• Bachelor’s or Master’s/PHD in Computer Science or related technical field, or relevant professional experience. 

#LI-AM3

About The Role

As a Senior Software Engineer, Android on the Roku Mobile App team, you will help shape the future of how millions of users interact with their Roku Streaming Devices. You’ll work on building intuitive, reliable, and highly performant Android experiences that allow customers to monitor and control Roku streaming devices from TVs to Players and beyond.

This role offers the opportunity to work across a modern, evolving tech stack including Kotlin, Compose, and Googles’s latest frameworks. You’ll collaborate closely with design, product, and cross-functional engineering teams to bring innovative features to life, improve performance, and make every day smart home interactions seamless.

You should be motivated by curiosity and initiative, eager to take ownership of features and run with them, while remaining grounded in a team-first, collaborative mindset.

About The Team

You will be joining a talented, high-performance team with a history of delivery. We are looking for someone who can help us keep up this pace and continue delivering high-quality app as we grow.

With so many people using our products globally, we’ve become well-known for products that “just work” right out of the box and integrate almost by magic. That doesn’t happen by accident, which is why we are committed to making sure our products aren’t just intuitive, they’re obvious

What You’ll Be Doing

• Design and build advanced applications and features for the Android platform
• Integrate with cloud APIs and local device communication protocols to control smart devices
• Write and maintain tests using frameworks such as JUnit and Espresso
• Collaborate with cross-functional teams to define, design, and ship new features for mobile devices, optimizing for touch experiences. Write well-designed, testable, and efficient code
• Debug, profile, and optimize app performance across a range of Android devices
• Participate in design and code reviews, helping elevate code quality across the team
• Stay up to date with Android platform capabilities, tools, and libraries, and propose how we can leverage them
• Contribute to roadmap planning, technical design, and release delivery

We’re Excited If You Have

• Professional Android development experience, ideally with Kotlin and/or Compose
• Strong experience shipping and maintaining production apps in the Play Store
• Proficiency in using AI tools (e.g., GitHub Copilot, ChatGPT) and experience with prompt engineering
• Experience working with IoT or networked device interactions is a big plus
• Familiarity with BLE, webs sockets, or MQTT protocols is a bonus
• Experience collaborating with cross-functional teams in agile environments
• Proficient in the Android development toolset
• Strong understanding of Android architecture, UI/UX patterns, and app lifecycle
• Excellent communication and debugging skills
• Bachelor’s or Master’s/PHD in Computer Science or related technical field

#LI-AM3

About the Role

You will be a SME and technical leader in engineering Infrastructure, productivity and enterprise tooling, partnering with globally distributed Engineering, Product and Security teams and systems.

What You’ll Be Doing

Roku is seeking a world class engineer to be a true force multiplier by owning the strategy, architecture, and long-term execution of engineering infrastructure, enterprise tooling, and AI-assisted workflow automation. This architect/strategist role drives org-wide improvements in engineering productivity, delivery throughput, quality, security posture, and cost efficiency by building platforms, working practices and automation (including AI/LLM-enabled capabilities) that scale across geographies and time zones.

Key Responsibilities

AI-First Automation & Intelligent Tooling

• Define and lead an AI-first automation roadmap for Engineering Infrastructure and Enterprise Tooling (e.g., reducing waste, accelerating reviews, improving incident response, increasing release confidence).
• Architect and ship AI/LLM-enabled workflow automation across the SDLC (e.g. risk assessment, automated build, test and deployment, intelligent test selection, change-impact analysis, auto-triage of build/test failures).
• Establish policies and guardrails for AI usage in internal tools: data handling, prompt/response logging, model/provider selection, evaluation, fallback behaviors, and abuse prevention.

Dev Productivity & Enterprise Tooling (Global Scale)

• Set technical direction and standards for the globally used developer tools, including build systems. Source code management, branching/release strategy, and self-service support tools.
• Architect and evolve, CI/CD and build/test pipelines using Jenkins, Docker, and build systems (Bazel /BitBake/Yocto  preferred) to support multi-site engineering environments.
• Own and scale test and quality workflows leveraging test management systems (e.g., TestRail or equivalent), enabling consistent traceability, reporting, and release sign-off across distributed teams.
• Drive Jira workflow design and automation (templates, guardrails, integrations) to provide consistent cross-org visibility and execution.

Workflow Automation (Cross-Functional, Cross-Geo)

• Design and implement automation spanning Engineering, Product, Marketing, and Partners (e.g., launch readiness, certification/release checklists, partner onboarding, incident/change workflows).
• Replace manual coordination with durable automation and integrations that work reliably across regions/time zones.

Security, Cost, Performance, and Reliability (Distributed Systems)

• Embed secure-by-default controls into pipelines and tooling (access control, secrets handling, audit trails, policy enforcement), including for AI-enabled systems.
• Improve build/test performance and reliability (build times, test duration, flake reduction, pipeline stability) using measurable KPIs and operational rigor.
• Drive cost efficiencies across tooling/infrastructure (compute utilization, caching strategies, license rationalization including AI/runtime costs and ROI tracking.
• This is a highly visible role and you will report directly to a Vice President of Engineering. This requires a very strong technical leader with experience in the development of consumer electronics devices. The right person for this role will have ability to collaborate well with engineering and partner teams.
• Own cross-team architectures and standards; drive adoption through influence, clear technical judgment, and sustained multi-quarter execution.
• Lead design reviews, mentor senior engineers, and unblock the hardest technical problems across distributed teams and systems.
• Provide long-term stewardship via roadmaps, operational maturity (runbooks/SLOs), and incident/postmortem practices suitable for 24/7 global operations.
• Establish yourself as the person others bring their hardest problems to

We’re Excited If You Have

• Bachelor’s in Computer Science or Computer Engineering, or equivalent experience
• Prior experience at Staff, Principal, or Architect level
• Ownership in platform/infrastructure, developer productivity, CI/CD, build systems, or workflow automation, including work spanning globally distributed teams and systems.
• Strong, hands-on knowledge of:

• • Git (workflows, branching strategies, release management)
  • Jenkins (CI/CD pipeline design, scaling, reliability)
  • Docker containers (reproducible build/test execution)

Build systems ( itBake/Yocto preferred)

• Jira (workflow design/automation, cross-team visibility)
• Test management systems (e.g., TestRail or equivalent)
• Demonstrated experience delivering automation at scale, including building platforms/components used by multiple teams.
• Strong systems thinking across security, reliability, performance, and cost tradeoffs.
• Excellent written communication (architecture docs, decision records, operating procedures).
• Experience building AI-assisted developer tooling (e.g., CI insights, test intelligence, code review automation, release risk scoring, incident copilots).
• Experience implementing evaluation/monitoring for AI systems (quality metrics, drift, offline test sets, human feedback loops).
• Extensive experience with software development on embedded Linux,  multi-process architectures and IPC mechanisms
• Experience working in large cross functional teams and ability to influence teams that don't report to you
• Ability to see the big picture while focused on short-term objectives and deliverables
• Ability to multi-task and drive parallel projects and distributed teams with tight deadlines

#LI-NM1

About the Role

You will be a SME and technical leader in engineering Infrastructure, productivity and enterprise tooling, partnering with globally distributed Engineering, Product and Security teams and systems.

What You’ll Be Doing

Roku is seeking a world class engineer to be a true force multiplier by owning the strategy, architecture, and long-term execution of engineering infrastructure, enterprise tooling, and AI-assisted workflow automation. This architect/strategist role drives org-wide improvements in engineering productivity, delivery throughput, quality, security posture, and cost efficiency by building platforms, working practices and automation (including AI/LLM-enabled capabilities) that scale across geographies and time zones.

Key Responsibilities

AI-First Automation & Intelligent Tooling

• Define and lead an AI-first automation roadmap for Engineering Infrastructure and Enterprise Tooling (e.g., reducing waste, accelerating reviews, improving incident response, increasing release confidence).
• Architect and ship AI/LLM-enabled workflow automation across the SDLC (e.g. risk assessment, automated build, test and deployment, intelligent test selection, change-impact analysis, auto-triage of build/test failures).
• Establish policies and guardrails for AI usage in internal tools: data handling, prompt/response logging, model/provider selection, evaluation, fallback behaviors, and abuse prevention.

Dev Productivity & Enterprise Tooling (Global Scale)

• Set technical direction and standards for the globally used developer tools, including build systems. Source code management, branching/release strategy, and self-service support tools.
• Architect and evolve, CI/CD and build/test pipelines using Jenkins, Docker, and build systems (Bazel /BitBake/Yocto  preferred) to support multi-site engineering environments.
• Own and scale test and quality workflows leveraging test management systems (e.g., TestRail or equivalent), enabling consistent traceability, reporting, and release sign-off across distributed teams.
• Drive Jira workflow design and automation (templates, guardrails, integrations) to provide consistent cross-org visibility and execution.

Workflow Automation (Cross-Functional, Cross-Geo)

• Design and implement automation spanning Engineering, Product, Marketing, and Partners (e.g., launch readiness, certification/release checklists, partner onboarding, incident/change workflows).
• Replace manual coordination with durable automation and integrations that work reliably across regions/time zones.

Security, Cost, Performance, and Reliability (Distributed Systems)

• Embed secure-by-default controls into pipelines and tooling (access control, secrets handling, audit trails, policy enforcement), including for AI-enabled systems.
• Improve build/test performance and reliability (build times, test duration, flake reduction, pipeline stability) using measurable KPIs and operational rigor.
• Drive cost efficiencies across tooling/infrastructure (compute utilization, caching strategies, license rationalization including AI/runtime costs and ROI tracking.
• This is a highly visible role and you will report directly to a Vice President of Engineering. This requires a very strong technical leader with experience in the development of consumer electronics devices. The right person for this role will have ability to collaborate well with engineering and partner teams.
• Own cross-team architectures and standards; drive adoption through influence, clear technical judgment, and sustained multi-quarter execution.
• Lead design reviews, mentor senior engineers, and unblock the hardest technical problems across distributed teams and systems.
• Provide long-term stewardship via roadmaps, operational maturity (runbooks/SLOs), and incident/postmortem practices suitable for 24/7 global operations.
• Establish yourself as the person others bring their hardest problems to

We’re Excited If You Have

• Bachelor’s in Computer Science or Computer Engineering, or equivalent experience
• Prior experience at Staff, Principal, or Architect level
• Ownership in platform/infrastructure, developer productivity, CI/CD, build systems, or workflow automation, including work spanning globally distributed teams and systems.
• Strong, hands-on knowledge of:

• • Git (workflows, branching strategies, release management)
  • Jenkins (CI/CD pipeline design, scaling, reliability)
  • Docker containers (reproducible build/test execution)

Build systems ( itBake/Yocto preferred)

• Jira (workflow design/automation, cross-team visibility)
• Test management systems (e.g., TestRail or equivalent)
• Demonstrated experience delivering automation at scale, including building platforms/components used by multiple teams.
• Strong systems thinking across security, reliability, performance, and cost tradeoffs.
• Excellent written communication (architecture docs, decision records, operating procedures).
• Experience building AI-assisted developer tooling (e.g., CI insights, test intelligence, code review automation, release risk scoring, incident copilots).
• Experience implementing evaluation/monitoring for AI systems (quality metrics, drift, offline test sets, human feedback loops).
• Extensive experience with software development on embedded Linux,  multi-process architectures and IPC mechanisms
• Experience working in large cross functional teams and ability to influence teams that don't report to you
• Ability to see the big picture while focused on short-term objectives and deliverables
• Ability to multi-task and drive parallel projects and distributed teams with tight deadlines

#LI-NM1

Who We Are

DoubleVerify is an Israeli-founded big data analytics company (Stock: NYSE: DV). We track and analyze tens of billions of ads every day for the biggest brands in the world.
We operate at a massive scale, handling over 100B events per day and over 1M RPS at peak, we process events in real-time at low latencies (ms) and analyze over 2.5M video years every day. We verify that all ads are fraud free, appear next to appropriate content, appear to people in the right geography and measure the viewability and user’s engagement throughout the ad’s lifecycle. 

We are global, with HQ in NYC and R&D centers in Tel Aviv, New York, Finland, Berlin, Belgium and San Diego. We work in a fast-paced environment and have a lot of challenges to solve. If you like to work in a huge scale environment and want to help us build products that have a huge impact on the industry, and the web - then your place is with us.

What You Will Do

We're looking for a talented Software Engineer with enthusiasm for AI/GenAI to join our innovation-focused team building agentic AI systems autonomous, reasoning-driven software agents capable of orchestrating complex tasks across tools, APIs, and data sources.

You'll design and build scalable backend systems that integrate large language models (LLMs) and other AI technologies into production-grade services. This role blends backend engineering, AI integration, and rapid prototyping, with room to learn, experiment, and deliver impactful, scalable solutions.

• Architect and implement distributed services that power AI-driven applications.
• Implement multi-step reasoning pipelines, retrieval-augmented generation (RAG), and domain-specific AI capabilities.
• Build robust APIs, plugins, and integrations enabling AI agents to interact with external systems and data sources.
• Create and refine proof-of-concepts, validating ideas quickly before scaling to production.
• Implement monitoring, evaluation, and logging systems to track AI-powered features in production.
• Work closely with product managers, designers, data scientists, and AI engineers to deliver user-focused solutions.
• Stay curious about emerging AI frameworks, tools, and best practices to improve reasoning, planning, and autonomy in backend services.

Who You Are

• Backend Specialist with a Passion for AI/GenAI, strong systems skills, and eagerness to grow in AI.
• 5+ years in Python /Java/Scala/C#/ Go
• Familiarity with LLM frameworks (LangChain, LangGraph, Haystack, etc.) or willingness to learn.
• Basic understanding of prompt engineering, vector databases, and retrieval-augmented generation (RAG).
• Solid knowledge of cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Proven track record in building scalable, distributed systems.
• Strong problem-solving, ownership, and collaboration skills.

Nice-to-Have Skills

•  Exposure to reinforcement learning, multi-agent systems, or autonomous planning.
• Interest in ML Ops, AI model deployment, and scaling AI workloads.
•  Experience with data engineering for AI (ETL pipelines, feature stores, embeddings).
•  Any experience building AI-powered platforms or agent-based systems.

#Hybrid#

Wir sind mehr als 2.000 Kolleg:innen in 22 Designstudios auf vier Kontinenten – ein hochgradig kollaboratives Team aus Expert:innen für Produkterlebnisse, digitales Marketing und immersive Technologien. Unsere Lösungen entstehen dort, wo Kreativität und Technologie zusammentreffen – mit einem klaren Fokus auf die Bedürfnisse und Erlebnisse der Nutzer:innen. Ob Augmented Reality, Digital Twins, KI-Ökosysteme, Omnichannel-Commerce oder integrierte Kampagnen: Wir schaffen Verbindungen zwischen Menschen und Marken – im B2B- ebenso wie im B2C-Bereich. 

Als Teil des globalen Technologieinnovators Infosys verfügen wir über die nötige Skalierung und Expertise, um große Ideen Wirklichkeit werden zu lassen – und sie weltweit umzusetzen. 

Wir sind eine Motion Picture & 3D Production mit Fokus auf hochwertige CGI- und Content-Produktion für starke Marken (u. a. Automotive, Fashion, Consumer Goods). Unser Sweet Spot: kreative Exploration mit GenAI – und wenn nötig kampagnenfähige, pixel-perfect Ergebnisse im Produktionsmaßstab. 

Deine Rolle 

Du bringst GenAI-Bildgenerierung und -Bildbearbeitung (v. a. ComfyUI) so in unsere CGI-/Compositing-Pipeline, dass aus Ideen schnell realistische, konsistente und markentaugliche Visuals werden. 

Das erwartet Dich 

1.) Look Development & Concept Exploration  

• Du entwickelst Bildwelten, Motive und Variationen für Kampagnen  
• Du arbeitest mit ComfyUI in bestehenden Graphen, pflegst sie und erweiterst sie für konkrete Use Cases (z. B. Environment/Background, Produktintegration, Serien-Varianten). 
• Du baust Prompt-Frameworks / Prompt-Baupläne, um Konsistenz und Qualität über Serien zu halten. 

2.) CGI Enhancement & “AI als Finish”  

• Du nutzt GenAI als Finish-Layer nach dem 3D: Enhancement, Compositing-Unterstützung, Details, Realismus, Konsistenz. 
• Du arbeitest eng mit 3D/CGI/Compositing zusammen (u. a. C4D, Maya, Unreal, Nuke, After Effects, Photoshop, Substance). 
• Du hilfst, typische Produktionsherausforderungen zu lösen (z. B. Produktgenauigkeit, Proportionen, Detailgrad). 

3.) Workflow-Qualität & Skalierung  

• Du setzt auf Batch/Automation in ComfyUI (Queues, Varianten, reproduzierbare Runs). 
• Du evaluierst Modelle/Ansätze (Qualität/Speed) und setzt sie passend zum Use Case ein 
• Du dokumentierst ComfyUI-Templates/Workflows und erstellst Best-Practice Guides, damit Teams sauber weiterarbeiten können. 
• Für kleine Automationen nutzt du gelegentlich Skripte/Helpers (Python/JS). Für größere Infrastruktur-/Engineering-Themen gibt es bei uns separate Engineering-Unterstützung. 

Das bringst Du mit 

• Hands-on Erfahrung mit GenAI im Imaging-Kontext, inklusive Bildgenerierung sowie gezielter Bearbeitung und Qualitätsverbesserung 
• Sichere Praxis mit ComfyUI, insbesondere node-basierte Workflows, saubere Graphen und Troubleshooting 
• Ausgeprägtes Verständnis von Bildgestaltung und Visual Quality, z. B. Komposition, Licht, Materialität und Stil 
• Erfahrung oder fundiertes Verständnis von CGI- und Compositing-Pipelines, inklusive Übergaben, Render-Logik und dem Weg vom Setup zum finalen Bild 
• Portfolio oder Arbeitsproben, die Realismus, Konsistenz und visuelle Qualität unter produktionsnahen Constraints belegen (über reine Prompt-Experimente hinaus) 
• Fließende Deutsch- und/oder Englischkenntnisse (mindestens B2-C1) sind Voraussetzung.

Was zusätzlich begeistert (Bonus, aber kein Muss)

• Git-Grundlagen (Versioning von Workflows/Configs) 
• Kleine Skripting-Skills (Python/JS) für Helpers 
• Erfahrung mit API-basierten Tools (Cloud) und/oder lokalen Setups (Compliance) 
• Automotive/Fashion/Consumer Goods Erfahrung (z. B. Produktinszenierung, Brand-Look, Konsistenz) 
• 3D Dataprep Know-how (CAD cleanup, UV/Material-Prep, Lighting Presets, AOVs/Depth) 

Wie wir arbeiten 

• Du arbeitest mit einem interdisziplinären Team (Creative Direction, CGI/3D, Motion/Comp, Engineering). 
• Typischer Review: 2 Feedbackschleifen (intern/Lead + Freigabe). 
• Qualität ist uns wichtig: kampagnenfähig / photoreal / pixel-perfect, aber wir unterscheiden klar zwischen Exploration und Final. 
• Primär remote innerhalb Deutschlands, mit ca. 2 Tagen/Monat vor Ort in Stuttgart. 
• Alltagssprache im Team ist überwiegend Deutsch – du musst nicht perfekt sein, aber kommunikationsfähig (Englisch geht selbstverständlich). 

Unsere lokalen Benefits 

• Flexible Arbeitszeiten  
• Arbeiten von wo es für dich passt. Zu Hause oder im Büro, ganz nach deinem Geschmack 
• Arbeit für starke Marken und Kund:innen, an die wir glauben  
• Zuschuss beim Urban Sports Club 
• Mitarbeitervorteile & Rabatte über Corporate Benefits 
• aufgeschlossene & nette Menschen in allen Teams 

Klingt nach Dir? Dann schnapp Dir Deinen Laptop und bewirb Dich – wir freuen uns, Dich auf unserer kreativen Reise dabei zu haben! Bitte sende uns: 

• CV  
• Portfolio/Showreel (sehr gern mit 2–3 Case Slides) 
• Optional sehr hilfreich: 1 Beispiel-Workflow (Screenshot/Export deines ComfyUI-Graphs + kurze Erklärung: Input → Schritte → Output → wie du Konsistenz & Produktgenauigkeit sicherst) 

Wir freuen uns besonders über Beispiele, in denen du Produkt-Treue, Proportionen und Realismus unter Constraints gelöst hast.  

Für uns zählt allein Deine Persönlichkeit und Deine beruflichen Fähigkeiten. Dein Geschlecht, Alter oder Aussehen, Deine Herkunft oder sexuelle Orientierung spielen für uns keine Rolle – wir sind offen für die Zusammenarbeit mit jeder Person. 

Beachte bitte: Dies ist eine Stellenanzeige der WongDoody GmbH mit Sitz in Deutschland. Über unsere Website oder andere Quellen kannst Du zu Stellenanzeigen gelangen, die von einer unserer WongDoody-Schwesterfirmen veröffentlicht wurden, mit denen wir weltweit gemeinsam unter der Marke "WongDoody" auftreten. Für jedes Stellenangebot ist ausschließlich das Unternehmen verantwortlich, das die jeweilige Anzeige veröffentlicht hat. Ansprechpartner:innen, erforderliche Angaben und geltende Bedingungen können jeweils abweichen. Hier kannst Du Dich darüber informieren, wie die WongDoody GmbH Deine im Bewerbungsprozess angegebenen personenbezogenen Daten verarbeitet.

Wenn Du Fragen zum Bewerbungsprozess hast, wende Dich gerne direkt an unser People & Culture-Team unter leonie.schaefer@odt.net

Tesco Media & Insight Platform is a partnership between Tesco, the UK’s largest grocery retailer, and dunnhumby. Fueled by first‑party behavioral data from over 23 million Clubcard holders, we help brands understand consumer behaviors and reach the right customers, at the right time, with the right message across the full marketing funnel. Our closed‑loop measurement connects what customers see with what they buy, helping brands Shape What Britain Buys and maximize the impact of every pound of media investment.

Roles and Responsibilities 

As a Senior AI Engineer, you will be a hands‑on technical contributor designing, building and operating production‑grade GenAI and agentic AI solutions that power Tesco Media & Insight Platform’s global products and services. You will work closely with the AI Engineering Manager, Product, Data Science and Engineering teams to turn business problems into secure, scalable, observable AI systems that deliver measurable value for brands and shoppers.

• Design and implement GenAI and agentic AI solutions on GCP, leveraging Vertex AI (models, endpoints, pipelines, vector search/RAG, Agent Builder) and core GCP services.
• Build AI agents and multi‑step agentic workflows, including tool calling, orchestration, and integrations with internal and external systems.
• Contribute to the design of MCP servers and agent‑to‑agent / agent‑to‑application protocols to enable safe, reliable automation of retail media and insight use cases.
• Work with the AI Engineering Manager and architects to define solution designs, interface contracts and non‑functional requirements (security, reliability, performance, cost).
• Implement security, privacy and governance controls in AI solutions, including safe prompt and tool design, data protection, secrets management and access control.
• Apply DevOps/MLOps practices: contribute to CI/CD pipelines for models, prompts and agents; use infrastructure as code; support environment management and automated testing.
• Implement observability for AI systems: instrument prompts, model calls, tools and agents with tracing, metrics and logs; build and maintain dashboards and alerts.
• Help define and run AI testing and evaluation strategies, including automated tests, offline and online evaluation, red‑teaming, regression suites and human‑in‑the‑loop review flows.
• Collaborate with Retail Media and Insight teams to understand use cases and data, and translate requirements into concrete AI components and services.
• Write high‑quality, well‑tested code in Python (and, where relevant, TypeScript/Java or similar) following team standards for readability, performance and reliability.
• Participate in code reviews, design reviews and incident post‑mortems, and contribute to continuous improvement of our AI engineering practices.
• Stay current on advances in LLMs, agentic frameworks and cloud AI services, and bring forward ideas for how they can be applied to Tesco Media & Insight Platform.

What you’ll need to succeed in the role

• Strong experience in software/data/ML engineering, with hands‑on delivery of AI/ML or LLM‑based solutions into production (not just prototypes).
• Practical experience on GCP and Vertex AI, including deploying models, building pipelines, and implementing RAG/vector search‑based solutions.
• Solid understanding of LLMs and foundation models: transformers at a high level, tokenization, embeddings, context windows, RAG, and the trade‑offs between fine‑tuning, adapters and prompt‑based approaches.
• Hands‑on experience building agentic workflows or AI agents (e.g. tool‑augmented chat, multi‑step workflows, or multi‑agent systems) using one or more modern frameworks or platforms.
• Good grasp of security and safety for AI systems, including prompt and tool design to reduce hallucinations and prompt injection, safe handling of sensitive data, and application‑level guardrails.
• Experience with DevOps/MLOps practices: CI/CD, version control, automated testing, infrastructure as code, monitoring and incident handling in a cloud environment.
• Strong programming skills in Python and experience building and consuming APIs; familiarity with microservices and event‑driven architectures is a plus.
• Ability to design and run evaluation and experimentation for AI features, including quantitative and qualitative measures and, where appropriate, human‑in‑the‑loop review.
• Strong problem‑solving skills, attention to detail, and a willingness to take ownership of complex technical challenges.
• Clear, proactive communication and the ability to collaborate effectively with product managers, data scientists, engineers and commercial stakeholders across locations.

About the Team

Razorpay's agentic products are scaling fast. Agent-powered onboarding, dashboard experiences, and automation workflows are live and growing, and the engineering teams building them are moving quickly. As we scale, we need shared infrastructure that lets every product team access the best model for each task without having to build routing, observability, or resilience logic themselves.

We are building an AI Inference Platform: a centralized layer that handles intelligent model routing, cost optimization, and quality observability across all of Razorpay's agentic products. The goal is simple. Product teams declare what kind of task they need done. The platform takes care of picking the right model, managing fallbacks, and tracking cost and quality. Teams stay focused on shipping features.

About the Role

As Lead AI Engineer on the platform side, you build the inference orchestration layer that sits between our product teams and their model providers. Routing, fallbacks, cost tracking, A/B testing for model swaps, and observability are all yours. Your customers are internal engineering teams, and your job is to give them a single reliable interface to every model the org uses while keeping the complexity of that routing layer off their plates.

You also own the observability and eval-in-production infrastructure: standardized tracing and cost dashboards across all agentic products, and the shadow-testing infrastructure that lets us validate model swaps safely before they reach production traffic.

What You’ll Build

• Build and operate a unified model gateway that abstracts provider complexity for product teams. Teams work with a clean interface; the platform handles routing, provider selection, and fallback logic under the hood
• Design and implement intelligent routing that matches each request to the right model based on task complexity, latency requirements, and cost targets. Not every call needs the same model
• Build resilience into the platform so provider outages, rate limits, and latency spikes are handled transparently. Agentic workflows stay up regardless of what happens upstream
• Own the observability layer across all AI-powered products: cost per call, latency distributions, token usage, and quality signals. Give product teams and leadership a clear view of how AI is performing and what it costs
• Build the infrastructure for safe model transitions: run new models alongside production, compare outputs, and roll out changes gradually with automated quality checks at every stage
• Drive continuous cost efficiency through caching strategies, request optimization, and per-team spend attribution so the org can scale AI usage without costs growing linearly with traffic

What We’re Looking For

• 5 to 8 years as a backend or platform engineer, with a track record of building API gateways, middleware, or developer platform services at scale. Strong in Go or Python
• Experience building high-availability, low-latency distributed systems: load balancing, circuit breakers, graceful degradation, retry logic, and observability using Prometheus, Grafana, OpenTelemetry, or equivalent
• Solid understanding of LLM APIs and token economics. You can design routing rules based on input/output token pricing, streaming vs. batch tradeoffs, and how prompt length affects both cost and latency
• You think in platform terms. You know the difference between building for end users and building for engineers, and you know that internal platform quality shows up in other teams’ velocity
• Familiarity with LLM orchestration and observability tooling: LiteLLM, Portkey, Langfuse, LangChain, or similar. You do not need to have used all of them, but you need to understand the landscape well enough to make good choices
• Experience with Kubernetes and distributed systems. GPU workload scheduling or ML serving infrastructure is a meaningful bonus

Why This Role is Different

• The platform you build becomes the backbone of every AI-powered product at Razorpay. Good infrastructure decisions here compound across every team and every workflow that ships on top of it
• You work on real scale from day one. The problems are concrete, the feedback loop is tight, and the impact of what you build shows up in production metrics quickly
• This role combines deep platform engineering with the emerging discipline of LLM infrastructure. It is a rare combination that puts you at the leading edge of how AI systems are built in production
• You are embedded in the decision-making, not downstream of it. You work directly with ML engineers and product teams, and your input shapes how the org approaches model selection, cost, and quality at every level
• You get genuine ownership over the architecture. This is a space where the right patterns are still being defined, and you have the scope to make meaningful design decisions rather than inherit them

Compensation & Benefits

Competitive compensation with ESOPs, comprehensive health insurance, learning and development budget, and all the perks of working at one of India’s leading fintech companies.

At Sonder, we believe that every person deserves to feel safe, supported, and empowered to be at their best - wherever they are. That’s why we’re redefining workplace health, safety, and wellbeing through a seamless blend of technology and human expertise. Sonder’s mobile platform provides 24/7, real-time support from a dedicated team of safety, medical, and mental health professionals - ensuring that our members receive immediate care when they need it most. In critical situations, we go beyond digital support, offering on-the-ground assistance to manage time-sensitive incidents.

By harnessing real-time insights, we enable organisations to take proactive steps toward a healthier, safer future, which leads directly to tangible bottom-line business outcomes.

An Exciting Time to Join Sonder! 

Since our founding in 2017, Sonder has experienced rapid growth, expanding operations across Australia, New Zealand, and the UK. Backed by Australia’s leading venture capital firms, Seek and Blackbird, we are well-capitalised and on a mission to scale globally, partnering with corporations, educational institutions, and government agencies to transform workplace wellbeing at scale. Our impact and scale: 1,000,000+ members across multiple countries 200+ team members, plus an extensive network of on-the-ground responders If you’re passionate about using technology and human expertise to drive meaningful change, join us in shaping the future of workplace wellbeing!

About the Role

Our Customer Insights and Measurement team at Sonder is looking for a Full Stack Engineer to help us build the next generation of wellbeing intelligence. We are looking for a builder who wants to own the entire journey, from crafting the customer-facing experience and data models to architecting the AI-first, human-in-the-loop insights that power our platform.

At Sonder, "Health and Wellbeing" isn't just a benefit; it’s our product. You’ll be building the tools that measure human impact, helping us move from reactive support to proactive, data-driven actions.

You will own the end-to-end journey of turning raw data into intelligent insights. On any given week, you might be building React-based dashboards, optimizing Snowflake transformations, or architecting multi-agent workflows that help our customers "talk" to their safety data.

What You’ll Be Doing:

Full Stack Development

• End-to-End Ownership: Build and maintain features from the database schema and Snowflake models through to the React UI.
• API Architecture: Design robust back-end services (Python/Node.js) that support data ingestion and high-concurrency reporting.

AI & Agentic Systems

• Agentic Workflows: Design and ship autonomous AI workflows using frameworks like LangGraph, CrewAI, or native tool-use patterns.
• RAG & Context Engineering: Build and optimize RAG pipelines, focusing on retrieval quality, chunking strategies, and metadata filtering.
• MCP Integration: Build and deploy Model Context Protocol (MCP) servers to bridge the gap between our internal data silos and LLM reasoning engines.
• AI Observability: Implement evaluation frameworks (e.g., LangSmith, Arize Phoenix) to monitor "vibe checks," latency, and cost in production.

Data Pipelines & Reporting

• Snowflake Mastery: Design and optimize tables and views that power customer-facing dashboards.
• Insight Automation: Use LLMs to automate the synthesis of complex safety data into actionable executive summaries.

What You will Bring

Must-Have:

• The "Builder" DNA: You are a heavy user of AI-assisted coding tools (Cursor, ClaudeCode, or Copilot) and have moved past the "experimental" phase into shipping production AI.
• Full Stack Fluency: Deep experience in React/Next.js and Python (preferred for AI) or Node.js.
• Data Engineering Literacy: Strong SQL skills and experience with data warehousing (Snowflake strongly preferred).
• Agentic Experience: You understand the difference between a basic prompt and a multi-step agentic loop involving tool-calling and structured outputs.
• Production Mindset: You know that "it worked on my machine" isn't enough; you care about LLM evaluation, prompt versioning, and error handling.

Nice-to-Have:

• Experience with vector databases (Pinecone, pgvector) and embedding-based search.
• Experience with dbt for data transformation.
• Familiarity with LangChain/LangGraph or other orchestration frameworks.
• A portfolio of "AI-first" side projects or contributions to open-source AI tools.
  
  

Why Join Sonder?

• Hybrid and flexible working – strike the right balance for your life and productivity
• Free Sonder app access for you and your family – 24/7 health, safety and wellbeing support
• 2 days study leave
• Paid parental leave – 12 weeks for primary carers and 4 weeks for secondary carers, with a supportive return-to-work program
• Employee Share Option Plan (ESOP) – share in Sonder’s success
• Wellbeing fund – $250 per year to spend your way
• Novated leasing and salary packaging options
• Weekly team perks – free coffee Tuesdays, catered lunch Thursdays, and a dog-friendly office
• Volunteer leave – 2 days per year to support causes that matter to you
• Regular social events and team bonding opportunities

Sonder is for Everyone

We’re committed to building a diverse and inclusive workplace. We encourage applications from people of all backgrounds, experiences, abilities and identities. If you need any support with your application or the recruitment process, please reach out – we’d love to hear from you.

Due to the nature of our industry, all Sonder employees are required to complete a National Police Check and Working With Children Check.

Staff Solutions Engineer 
Location: Bengaluru, Karnataka (Hybrid) 

Role Overview 

As a Staff Solutions Engineer, you are a hands-on software engineer who leads customer engagements from a technical pod while remaining deeply involved in design and implementation. 

You will own the technical success of customer deployments built on JazzX’s AGI platform—leading architecture, implementation, and delivery while working directly with enterprise customers. This role is designed for engineers who enjoy building real systems, guiding other engineers, and taking accountability for outcomes in complex customer environments. 

It is a delivery-focused engineering leadership role that combines deep technical execution with customer-facing ownership. 

You will: 

• Lead customer engagements as the technical owner for a delivery pod. 

• Design and implement production-grade enterprise systems using JazzX’s platform. 

• Apply GenAI and LLM-based capabilities (e.g., RAG, agent workflows) as part of scalable, reliable solutions. 

• Partner with product, platform, and research teams across the full solution lifecycle. 

• Act as the primary technical escalation point for customer deployments. 

• Influence platform evolution by feeding real-world learnings back into reusable components and patterns. 

• Set a high engineering bar through hands-on contribution, design leadership, and mentorship. 

Key Responsibilities 

Hands-On Software Engineering 

• Write and review production-quality code across backend services, APIs, and orchestration layers. 

• Make architectural decisions balancing scalability, performance, security, and long-term maintainability. 

• Design and build robust integrations with multiple third-party systems using RESTful APIs, event-driven interfaces, and data pipelines in complex enterprise environments. 

• Ensure solutions meet production standards for reliability, observability, and operational readiness. 

Applied GenAI & Agentic Systems 

• Apply a strong understanding of LLM behavior, capabilities, and limitations to design reliable, production-ready systems. 

• Build and orchestrate agentic workflows that coordinate multiple steps, tools, and decision points to achieve complex goals. 

• Design prompt strategies, tool interfaces, and control flows that enable agents to reason, act, and recover from failures. 

• Integrate LLMs into larger software systems with clear boundaries, guardrails, and observability. 

• Evaluate and iterate on agent behavior using real-world signals such as correctness, latency, cost, and user outcomes. 

• Collaborate with platform and research teams to validate emerging agent frameworks and reasoning approaches in customer environments. 

Customer Delivery Leadership 

• Lead technical execution for customer POCs, pilots, and production rollouts. 

• Work closely with customer engineering and IT teams to integrate JazzX into existing enterprise ecosystems. 

• Troubleshoot complex integration, data, and system issues, owning resolution end-to-end. 

Staff-Level Impact 

• Lead and mentor engineers within the delivery pod, providing technical direction and feedback. 

• Establish and reinforce best practices for customer-facing engineering. 

• Turn customer insights into reusable architectures, templates, and delivery standards. 

Qualifications 

Must-Have 

• 9+ years of professional software engineering experience building and operating production systems. 

• Strong proficiency in Python with a proven track record of writing maintainable, well-tested code. 

• Experience designing and building backend services, APIs, and distributed systems. 

• Practical experience applying GenAI or LLM-based systems in real-world applications (e.g., RAG pipelines, agent workflows, LLM-backed services). 

• Experience leading or owning technical delivery for customer-facing projects. 

• Strong understanding of system reliability, observability, and operational best practices. 

• Excellent communication skills and ability to collaborate with engineering, product, and customer stakeholders. 

• Willingness to travel up to 20% for key customer engagements. 

Nice-to-Have 

• Experience delivering software in regulated or policy-heavy domains (e.g., finance, lending, healthcare, insurance). 

• Familiarity with vector databases, semantic search, or knowledge retrieval systems. 

• Experience contributing to shared libraries, internal platforms, or reusable engineering components. 

• Prior experience in a fast-paced startup or early-stage product environment. 

Attributes We Value 

• Hands-On Leadership: You lead by building, reviewing, and guiding—not by delegating everything. 

• Engineering Excellence: You care deeply about correctness, reliability, and long-term maintainability. 

• Customer Empathy: You understand enterprise constraints and design systems accordingly. 

• Ownership & Accountability: You take responsibility for outcomes, not just tasks. 

• Collaboration & Mentorship: You raise the bar for those around you. 

Staff Solutions Engineer 
Location: Bengaluru, Karnataka (Hybrid) 

Role Overview 

As a Staff Solutions Engineer, you are a hands-on software engineer who leads customer engagements from a technical pod while remaining deeply involved in design and implementation. 

You will own the technical success of customer deployments built on JazzX’s AGI platform—leading architecture, implementation, and delivery while working directly with enterprise customers. This role is designed for engineers who enjoy building real systems, guiding other engineers, and taking accountability for outcomes in complex customer environments. 

It is a delivery-focused engineering leadership role that combines deep technical execution with customer-facing ownership. 

You will: 

• Lead customer engagements as the technical owner for a delivery pod. 

• Design and implement production-grade enterprise systems using JazzX’s platform. 

• Apply GenAI and LLM-based capabilities (e.g., RAG, agent workflows) as part of scalable, reliable solutions. 

• Partner with product, platform, and research teams across the full solution lifecycle. 

• Act as the primary technical escalation point for customer deployments. 

• Influence platform evolution by feeding real-world learnings back into reusable components and patterns. 

• Set a high engineering bar through hands-on contribution, design leadership, and mentorship. 

Key Responsibilities 

Hands-On Software Engineering 

• Write and review production-quality code across backend services, APIs, and orchestration layers. 

• Make architectural decisions balancing scalability, performance, security, and long-term maintainability. 

• Design and build robust integrations with multiple third-party systems using RESTful APIs, event-driven interfaces, and data pipelines in complex enterprise environments. 

• Ensure solutions meet production standards for reliability, observability, and operational readiness. 

Applied GenAI & Agentic Systems 

• Apply a strong understanding of LLM behavior, capabilities, and limitations to design reliable, production-ready systems. 

• Build and orchestrate agentic workflows that coordinate multiple steps, tools, and decision points to achieve complex goals. 

• Design prompt strategies, tool interfaces, and control flows that enable agents to reason, act, and recover from failures. 

• Integrate LLMs into larger software systems with clear boundaries, guardrails, and observability. 

• Evaluate and iterate on agent behavior using real-world signals such as correctness, latency, cost, and user outcomes. 

• Collaborate with platform and research teams to validate emerging agent frameworks and reasoning approaches in customer environments. 

Customer Delivery Leadership 

• Lead technical execution for customer POCs, pilots, and production rollouts. 

• Work closely with customer engineering and IT teams to integrate JazzX into existing enterprise ecosystems. 

• Troubleshoot complex integration, data, and system issues, owning resolution end-to-end. 

Staff-Level Impact 

• Lead and mentor engineers within the delivery pod, providing technical direction and feedback. 

• Establish and reinforce best practices for customer-facing engineering. 

• Turn customer insights into reusable architectures, templates, and delivery standards. 

Qualifications 

Must-Have 

• 9+ years of professional software engineering experience building and operating production systems. 

• Strong proficiency in Python with a proven track record of writing maintainable, well-tested code. 

• Experience designing and building backend services, APIs, and distributed systems. 

• Practical experience applying GenAI or LLM-based systems in real-world applications (e.g., RAG pipelines, agent workflows, LLM-backed services). 

• Experience leading or owning technical delivery for customer-facing projects. 

• Strong understanding of system reliability, observability, and operational best practices. 

• Excellent communication skills and ability to collaborate with engineering, product, and customer stakeholders. 

• Willingness to travel up to 20% for key customer engagements. 

Nice-to-Have 

• Experience delivering software in regulated or policy-heavy domains (e.g., finance, lending, healthcare, insurance). 

• Familiarity with vector databases, semantic search, or knowledge retrieval systems. 

• Experience contributing to shared libraries, internal platforms, or reusable engineering components. 

• Prior experience in a fast-paced startup or early-stage product environment. 

Attributes We Value 

• Hands-On Leadership: You lead by building, reviewing, and guiding—not by delegating everything. 

• Engineering Excellence: You care deeply about correctness, reliability, and long-term maintainability. 

• Customer Empathy: You understand enterprise constraints and design systems accordingly. 

• Ownership & Accountability: You take responsibility for outcomes, not just tasks. 

• Collaboration & Mentorship: You raise the bar for those around you. 

Staff Solutions Engineer 
Location: Bengaluru, Karnataka (Hybrid) 

Role Overview 

As a Staff Solutions Engineer, you are a hands-on software engineer who leads customer engagements from a technical pod while remaining deeply involved in design and implementation. 

You will own the technical success of customer deployments built on JazzX’s AGI platform—leading architecture, implementation, and delivery while working directly with enterprise customers. This role is designed for engineers who enjoy building real systems, guiding other engineers, and taking accountability for outcomes in complex customer environments. 

It is a delivery-focused engineering leadership role that combines deep technical execution with customer-facing ownership. 

You will: 

• Lead customer engagements as the technical owner for a delivery pod. 

• Design and implement production-grade enterprise systems using JazzX’s platform. 

• Apply GenAI and LLM-based capabilities (e.g., RAG, agent workflows) as part of scalable, reliable solutions. 

• Partner with product, platform, and research teams across the full solution lifecycle. 

• Act as the primary technical escalation point for customer deployments. 

• Influence platform evolution by feeding real-world learnings back into reusable components and patterns. 

• Set a high engineering bar through hands-on contribution, design leadership, and mentorship. 

Key Responsibilities 

Hands-On Software Engineering 

• Write and review production-quality code across backend services, APIs, and orchestration layers. 

• Make architectural decisions balancing scalability, performance, security, and long-term maintainability. 

• Design and build robust integrations with multiple third-party systems using RESTful APIs, event-driven interfaces, and data pipelines in complex enterprise environments. 

• Ensure solutions meet production standards for reliability, observability, and operational readiness. 

Applied GenAI & Agentic Systems 

• Apply a strong understanding of LLM behavior, capabilities, and limitations to design reliable, production-ready systems. 

• Build and orchestrate agentic workflows that coordinate multiple steps, tools, and decision points to achieve complex goals. 

• Design prompt strategies, tool interfaces, and control flows that enable agents to reason, act, and recover from failures. 

• Integrate LLMs into larger software systems with clear boundaries, guardrails, and observability. 

• Evaluate and iterate on agent behavior using real-world signals such as correctness, latency, cost, and user outcomes. 

• Collaborate with platform and research teams to validate emerging agent frameworks and reasoning approaches in customer environments. 

Customer Delivery Leadership 

• Lead technical execution for customer POCs, pilots, and production rollouts. 

• Work closely with customer engineering and IT teams to integrate JazzX into existing enterprise ecosystems. 

• Troubleshoot complex integration, data, and system issues, owning resolution end-to-end. 

Staff-Level Impact 

• Lead and mentor engineers within the delivery pod, providing technical direction and feedback. 

• Establish and reinforce best practices for customer-facing engineering. 

• Turn customer insights into reusable architectures, templates, and delivery standards. 

Qualifications 

Must-Have 

• 9+ years of professional software engineering experience building and operating production systems. 

• Strong proficiency in Python with a proven track record of writing maintainable, well-tested code. 

• Experience designing and building backend services, APIs, and distributed systems. 

• Practical experience applying GenAI or LLM-based systems in real-world applications (e.g., RAG pipelines, agent workflows, LLM-backed services). 

• Experience leading or owning technical delivery for customer-facing projects. 

• Strong understanding of system reliability, observability, and operational best practices. 

• Excellent communication skills and ability to collaborate with engineering, product, and customer stakeholders. 

• Willingness to travel up to 20% for key customer engagements. 

Nice-to-Have 

• Experience delivering software in regulated or policy-heavy domains (e.g., finance, lending, healthcare, insurance). 

• Familiarity with vector databases, semantic search, or knowledge retrieval systems. 

• Experience contributing to shared libraries, internal platforms, or reusable engineering components. 

• Prior experience in a fast-paced startup or early-stage product environment. 

Attributes We Value 

• Hands-On Leadership: You lead by building, reviewing, and guiding—not by delegating everything. 

• Engineering Excellence: You care deeply about correctness, reliability, and long-term maintainability. 

• Customer Empathy: You understand enterprise constraints and design systems accordingly. 

• Ownership & Accountability: You take responsibility for outcomes, not just tasks. 

• Collaboration & Mentorship: You raise the bar for those around you. 

Tenable Operational Technology (OT) Security

Tenable OT Security was established through the acquisition of a pioneering
Israeli cybersecurity startup, marking a major milestone in Tenable’s
mission to provide proactive security for the world's most sensitive
environments. Our solution offers critical visibility and risk management
for Industrial Control Systems (ICS/SCADA), protecting essential
infrastructures such as power plants, manufacturing floors, and smart
buildings. While traditionally an on-premises solution designed to ensure
operational continuity and prevent costly downtime, we are now evolving our
technology to deliver market-leading risk visibility through advanced
architectures and AI-driven capabilities. By combining deep on-premises
expertise with proactive AI insights, we empower organizations to identify
threats and network anomalies before any damage occurs

Your Opportunity:
As a Fullstack /Frontend oriented  Engineer on our team, you will be a key
contributor to our OT security platform, building from the ground up using
the latest versions of Angular. We are looking for a developer who is
equally comfortable defining new technical foundations as they are diving
into daily feature development and ticket execution. You will work as a
core member of an agile team, partnering with Product and Design to
translate requirements into user-centric interfaces, while also having the
curiosity to touch the Backend and work with APIs. This role is ideal for a
proactive engineer who enjoys the end-to-end process—from integrating
AI-driven insights to delivering on product goals—ensuring a seamless
experience for our customers..

What you'll need:

• 3+ years of experience as a Front-end Developer, with a strong focus on  the Angular Framework.
• Proficiency in TypeScript, JavaScript, and CSS (experience with SASS/LESS is a plus).
• Deep knowledge of performance optimization techniques and browser troubleshooting.
• Active engagement with AI development tools (Copilot, Cursor, Claude, etc.) with a strong emphasis on prompt engineering.
• Critical thinking skills, a sense of ownership, and a team-player mentality.
• Excellent interpersonal and communication skills.
• Proven experience in Backend development and full-stack ownership; we are open to any programming language for the Backend.

Not sure whether to apply? Just do it!

Building a great AI assistant is only half the battle – knowing whether it's actually great is the other half. Our team owns the measurement and quality layer that make Glean's Assistant and Agents reliably better over time: evaluation pipelines, quality evalsets, LLM-powered judges, agent observability, and the tooling engineers use to understand what changed and why. It's a rare combination of infrastructure engineering, applied ML, and direct product impact. If you care deeply about quality and want to build the systems that make it measurable, this role is for you.

You will: 

• Design and curate evaluation datasets – sampling strategies, query diversity, and golden sets that give reliable, representative coverage of real assistant behavior.
• Build and maintain large-scale evaluation pipelines that measure assistant quality across thousands of real user queries.
• Build LLM-powered judges that score metrics like correctness, completeness, and response quality, and align them against human judgment.
• Evaluate new models and product changes before they ship – providing the quality signal that gates launches and prevents regressions.
• Build observability infrastructure for AI agents: trace enrichment, data pipelines, and dashboards that make assistant behavior inspectable.
• Close the loop between quality measurement and improvement using eval results, customer feedback, and techniques like automated prompt iteration to help drive concrete gains in assistant behavior.
• Collaborate with engineers across the company to make evals a first-class part of how we ship.

About you:

• 2+ years of software engineering experience with strong coding skills.
• Strong backend fundamentals in Go and Python; comfortable with distributed data pipelines.
• Experience working with LLM evaluation, reinforcement learning from human feedback, natural language processing, or other large systems involving machine learning.
• Analytically rigorous – you think carefully about what offline metrics actually predict about real user experience.
• Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company
• You care about quality – not just in the systems you build, but in the product you're helping measure and improve.

Location: 

• This role is hybrid (3-4 days a week in one of our SF Bay Area offices)

Compensation & Benefits:

The standard base salary range for this position is $200,000 - $300,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.

We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

#LI-HYBRID

Building a great AI assistant is only half the battle – knowing whether it's actually great is the other half. Our team owns the measurement and quality layer that make Glean's Assistant and Agents reliably better over time: evaluation pipelines, quality eval-sets, LLM-powered judges, agent observability, and the tooling engineers use to understand what changed and why. It's a rare combination of infrastructure engineering, applied ML, and direct product impact. If you care deeply about quality and want to build the systems that make it measurable, this role is for you.

You will: 

• Design and curate evaluation datasets – sampling strategies, query diversity, and golden sets that give reliable, representative coverage of real assistant behavior.
• Build and maintain large-scale evaluation pipelines that measure assistant quality across thousands of real user queries.
• Build LLM-powered judges that score metrics like correctness, completeness, and response quality, and align them against human judgment.
• Evaluate new models and product changes before they ship – providing the quality signal that gates launches and prevents regressions.
• Build observability infrastructure for AI agents: trace enrichment, data pipelines, and dashboards that make assistant behavior inspectable.
• Close the loop between quality measurement and improvement using eval results, customer feedback, and techniques like automated prompt iteration to help drive concrete gains in assistant behavior.
• Collaborate with engineers across the company to make evals a first-class part of how we ship.