Staff Software Engineer: Applied AI

Every day, thousands of shipments cross borders, change hands, and hit unexpected problems. For decades, fixing those problems meant phone calls, emails, and humans heroically firefighting. We think that's about to change completely.

We've been building AI agents that spot trouble before it happens, reroute shipments, and keep goods moving—with our team of experts in the loop where it counts. The early results have been jaw-dropping. We're now going all in on a future where supply chains run themselves, and we're looking for the people who want to build that future with us.

This isn't a role where you join a team and pick up tickets. You'll find the highest-leverage problems, design the solutions, and ship them to operators moving freight across 112 countries. If that sounds like your idea of a good time, read on.

What You'll Do

You'll build the cutting-edge agents and AI-powered applications that make Flexport's operations smarter, faster, and increasingly autonomous. That means:

• Designing and shipping end-to-end AI agents that handle real logistics work—customs compliance, document processing, exception management, and more
• Crossing organizational boundaries to understand problems deeply, align stakeholders, and get things done without waiting for permission
• Moving fast from idea to production, treating every deployment as a learning opportunity
• Working directly with operators, domain experts, and leadership to turn ambiguous problems into shipped solutions

You Should Have

• 10+ years of software engineering experience; you've built with LLMs extensively—whether in production, side projects, or just because you couldn't stop yourself
• Strong product instincts: you can identify what's worth building, not just execute on a spec
• LLM fluency: agent patterns, RAG, prompt engineering, tool use, evaluation. You know what works in production and what looks good in demos
• Full-stack capability in TypeScript and Next.js—you can own a feature end to end
• An entrepreneurial drive: you thrive in ambiguity, move fast, and don't wait to be told what to do
• Excellent communication: you can work across teams and disciplines to get alignment and unblock yourself
• An audacious appetite for impact: you're not here to maintain—you're here to change how global trade works

Nice to Have

• Experience with workflow orchestration (Temporal, etc.)
• Experience building internal tools or operator-facing applications

How We Work

• We come to the office 3 times a week to hang out, whiteboard, and ship together
• We have the latest hardware and software—including frontier AI models on day one
• We're agile, but not dogmatic. Teams decide how they work best
• Stack: Next.js, TypeScript, Postgres, Snowflake. For AI: Anthropic, OpenAI, Google AI APIs

Why This Role Is Special

• Your work is visible: This is a small, senior team reporting directly to the VP of Engineering. What you build gets noticed, and your ideas shape the direction
• Real stakes: thousands of containers, 112 countries, $19 billion of goods. Your agents will have immediate, measurable impact
• Full ownership: from problem definition to production deployment, it's yours
• You're early: the playbook for applied AI in enterprise logistics doesn't exist yet—you'll help write it

What's in it for you: 

• An opportunity to contribute to one of the fastest-growing companies, where you’ll have the chance to create a global impact while being a part of a  thriving multinational environment 
• Daily catered lunches incl. vegetarian options, breakfast, snacks and soft drinks available in our office on daily basis 
• Commute expenses: Flexport will cover  home-office commuting costs for employees living outside of Amsterdam
• 25 working days as vacation days based on full time employment.
• Health insurance: Flexport offers a collective health insurance plan including a basic package and any available additional packages. Your monthly premium is fully paid by Flexport. 
• A defined pension contribution scheme
• Equity program: every team member becomes a shareholder, aligning our success with yours. As a private company in a multi-trillion dollar industry, you have a direct stake in our collective growth and success.
• Employee Assistance Program through Aetna Resources for Living: Flexport provides an employer-sponsored program at no cost to you and your household members
• Parental leave benefit: Flexport is here to support you and your families in one of the most important times in life – the birth of a child! Our parental leave program allows both mothers and partners to take time off from work for pregnancy, childbirth, and to bond with your new child.

The AI & Automation Lead at Suitsupply, you'll play a crucial role in deploying and maintaining Automation solutions to support Suitsupply’s ambitious growth plans. As an Automation Lead, you collaborate with cross-functional teams to understand business requirements and implement effective solutions that enhance their business processes, automate workflows, and overall performance. 

What you will do: 

• Identify opportunities and implement automations of processes within different functional areas. 
• Context (prompt) engineer/Low-Code solutions for existing manual or inefficient areas of works that will yield significant time savings to teams. 
• Improve existing automation processes using workflows, validation rules, process builder, and other automation tools to improve efficiency. 
• Evaluate, and help implement best in market AI or other SaaS tools that will dramatically improve the speed and effectiveness of teams. 
• Conduct training sessions to ensure all team members are proficient in using new processes and/or tools 

Who you are: 

• Proven experience (3-5 years) as a Automation/Context Engineer or similar role is preferred. Keen interest in AI and emerging AI tools is a must.  
• Strong commercial understanding of business processes and best practices. 
• Proficiency in Context engineering/automation tools such as Cursor, Claude Code, LLMs etc.  
• Experience with data management and structures
• Detail oriented problem solver with string analytical skills 
• Strong communication and interpersonal skills to interact with cross-functional teams effectively 
• Professional understanding in Python is required
• Ability to adapt to a fast-paced and dynamic work environment 

What you will get

• Autonomy: We empower you to take ownership, make meaningful decisions, and drive impact without layers of sign-off.
• Growth: We see your potential as a key asset. At Suitsupply, you’ll have abundant opportunities to learn, grow, and excel in a supportive environment that encourages development at every step.
• Corporate Social Responsibility: Our commitment to sustainability and ethical business is unwavering. We work exclusively with suppliers who uphold the highest standards, in alignment with the International Labour Organization.
• Style: Immerse yourself in a world of beautifully crafted, high-quality products, and enjoy a 40% discount on Suitsupply products.

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We are now building services and agentic tools that provide AI coding agents and end users with deeper context about codebases. Our code retrieval service already delivers meaningful improvements in agent speed and task performance, and we aim to push this further – extracting richer insights than snippets alone at the scale of several hundred thousand repositories. 

We are looking for an AI Engineer who can design and implement agentic tools from scratch, bring them to the end users, and make coding with agents smarter, faster, and more reliable.

In this role, you will:

• Translate product needs into agentic tools and services and ship them to production.
• Scale prototypes to large numbers of users.
• Improve and test our semantic search service.
• Build evaluation pipelines for code retrieval and coding task performance.

We’ll be happy to have you on our team if you have:

• At least five years of hands-on NLP experience.
• Experience in information retrieval systems.
• Strong experience in LLM prompt and tool engineering, as well as with AI agents.
• Solid programming skills in Python and/or Kotlin (and the willingness to learn the language you’re unfamiliar with).
• Experience building and operating production-grade software systems.

We’d be especially thrilled if you have:

• Experience developing in Kotlin or Java.
• Previously worked with code intelligence (e.g. AST, symbol graphs).

#LI-DNI

An overview of this role

As a Staff Backend Engineer (Python) on the Duo Chat team in AI Engineering, you'll lead the backend architecture that powers GitLab Duo Chat across the GitLab DevSecOps platform. You'll solve hard problems in building reliable, secure, and scalable AI-powered chat workflows so customers can plan, write, review, and secure code faster, with confidence. This is a hands-on technical leadership role where you'll set direction for how we integrate and evolve large language model providers (including Google Vertex AI) across Ruby on Rails and Python services, raise the bar on observability and testing, and guide the team through ambiguous, high-impact technical decisions. Over your first year, you'll be expected to drive key architectural choices, reduce technical debt that slows iteration, and help the team ship durable improvements to response quality, reliability, and maintainability.

Some examples of our projects:

• Integrate new generative AI models and providers into GitLab Duo Chat to expand capabilities and improve response quality
• Improve debugging, observability, and test coverage for AI-powered chat workflows to increase reliability at scale

What you'll do

• Define the technical architecture and technical roadmap for the Duo Chat group, aligning backend execution with product direction and engineering priorities
• Solve the highest-scope and most ambiguous backend problems, delivering secure, well-tested, performant solutions with minimal guidance
• Integrate and extend generative AI capabilities in GitLab Duo Chat, including large language models (LLMs) and providers such as Google Vertex AI
• Develop, ship, and maintain backend features across Python and Ruby on Rails services that power Duo Chat experiences across the GitLab platform
• Design, implement, and review GraphQL application programming interface (API) contracts and supporting backend logic to ensure reliability, scalability, and clear frontend integrations
• Improve observability, debugging workflows, and incident readiness by strengthening logging, tracing, and production troubleshooting practices
• Drive code quality and long-term maintainability by setting internal standards, leading code reviews, and identifying and reducing technical debt
• Mentor engineers across the team and participate in Tier 2 on-call rotations, contributing to root cause analysis and follow-up improvements to resiliency and testing (including RSpec)

What you'll bring

• Production experience building and operating backend services in Python, including background jobs, APIs, and data models
• Ability to define and evolve technical architecture by weighing trade-offs, selecting patterns and tools, and setting a clear technical direction for others to follow
• Experience setting and driving a technical roadmap in partnership with product and engineering stakeholders
• Proficiency designing and maintaining REST and/or GraphQL APIs with attention to scalability, maintainability, and backward compatibility
• Hands-on experience integrating large language models into applications, including prompt design and building features powered by generative AI
• Strong SQL skills and experience working with relational databases such as PostgreSQL, including efficient queries and data modeling
• Experience mentoring engineers through code review, architectural guidance, and shared standards, and communicating complex technical decisions in a clear, async-first way
• Comfort contributing in a mature codebase across Python and Ruby on Rails, with openness to learning and applying transferable skills from related technologies or domains

About the team

The Duo Chat team sits within GitLab's AI Engineering organization and is responsible for building and evolving GitLab Duo Chat, the AI-powered chat experience embedded across the GitLab DevSecOps platform. You'll work with a small, cross-functional group of backend, frontend, and AI specialists who collaborate asynchronously across time zones, using GitLab issues, merge requests, and documentation as the primary way of working. The team focuses on integrating and scaling generative AI capabilities (including providers like Google Vertex AI), improving reliability and performance, and strengthening debugging, observability, and testing workflows so customers can safely use AI to plan, write, review, and secure their code across GitLab.

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. 

Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.
• Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.
• Establishing MLOps practices, including orchestration, observability, and experiment tracking.
• Collaborating with the engineering team on system design and with JetBrains Research on the research agenda.
• Defining hiring criteria, growing the ML team, and shaping the ML team culture.

We expect you to have:

• A proven track record as an ML/AI Lead.
• At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent.
• Vector databases and retrieval-augmented generation (RAG) patterns.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal. 

Our ideal candidate would have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• The ability to think strategically about product-led AI, beyond just training models in isolation.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.

#LI-KP1

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.

Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior AI/ML Engineer to build and evolve the ML-powered systems at the heart of our product.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction and retrieval, and subsequent reasoning.
• Creating datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving AI agents, which will involve prompt engineering, model selection, and inference optimization.
• Contributing to our MLOps practices, including orchestration, observability, and experiment tracking.

We expect you to have:

• At least four years of experience building ML/AI systems in production environments, with hands-on LLM experience.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangGraph, Pydantic AI, or an equivalent.
• Retrieval-augmented generation (RAG) patterns and vector databases.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• Opportunities to publish research at top venues in collaboration with JetBrains Research.

#LI-DNI

About the Role

We’re looking for a Junior Security Operations Engineer who is AI-Forward to help scale and modernize our SecOps program. This is a hands-on, builder role for someone who will design and ship the security tooling that powers our triage, investigations, and response workflows.

You’ll report to the Technical Operations Director and work alongside our GRC lead to improve our vulnerability intake, threat response, darkweb posture, and internal security tooling. A core part of this role is building AI-assisted security tooling: triage agents that pre-classify bug bounty reports, investigation copilots that pull context from logs and SIEM data, response workflows that draft remediation steps and track them to closure. You’ll spend as much time wiring up that tooling as you will reproducing vulnerabilities and working incidents.

This role suits someone who thrives in a lean, high-impact environment, has strong opinions on where humans add value versus where tooling should take over, and wants to shape how a modern security team operates.

What You’ll Do

Triage & Vulnerability Management

• Review incoming vulnerability reports from our bug bounty intake; reproduce and document valid issues for engineering teams.
• Build the tooling that improves signal-to-noise: automate duplicate detection, spam filtering, and abuse flagging so humans only touch what’s worth touching.
• Act on DAST findings: coordinate remediation, verify fixes, and re-test.
• Track remediation timelines for critical vulnerabilities and keep stakeholders honest on SLAs.

Threat Response & Monitoring

• Monitor and respond to EDR and cloud security alerts; investigate, contain, and document.
• Analyze darkweb findings and credential exposures; shape our darkweb monitoring practices and tooling over time.
• Improve detection coverage: tune noisy rules, close gaps, and enrich alerts with context so responders spend time on decisions, not data gathering.
• Help configure and tune DLP, SIEM, and AI security tooling.

Security Tooling (core to this role)

• Build AI-assisted triage tooling that pre-classifies bug bounty reports, flags duplicates, and routes real issues to the right engineering team with reproduction context attached.
• Build investigation tooling: LLM-backed copilots and Slack bots that pull alert context, correlate signals across sources, and surface what actually matters.
• Build response tooling: workflows that draft remediation steps, generate evidence artifacts, and track issues to closure across the teams that own them.
• Evaluate emerging AI security tooling and bring what’s genuinely useful into the stack; retire what isn’t.
• Apply a security-minded lens to our own AI usage: prompt injection, data exfiltration, model misuse, and the guardrails that go around them.

Compliance & Cross-Functional

• Support audit evidence collection for SOC 2, ISO 27001, and PCI DSS.
• Partner with ITOps to verify patches, endpoint coverage, and access hygiene.

You May Be a Good Fit If You Have

• Previous experience in a SecOps, Security Analyst, or Threat Response role.
• Proven ability to understand and reproduce technical vulnerabilities. You can read a bug report and tell whether it’s real.
• Experience with bug bounty triage (HackerOne, Bugcrowd, or similar).
• Hands-on exposure to SIEM, EDR, and DLP tools in production environments.
• A genuine, demonstrated interest in applying AI/LLMs to security work: side projects, internal tooling, prompt engineering, agent frameworks, anything that shows you’ve actually built with this stuff.
• Scripting and automation skills in Python, Bash, or similar. You reach for code before you reach for a checklist.
• Comfort working autonomously across time zones and asynchronously.
• Strong written communication. You can turn a messy investigation into a clear, defensible writeup.

Bonus Points For

• Experience building LLM agents, RAG pipelines, or Slack bots backed by OpenAI / Anthropic / open-source models.
• Detection engineering experience (Sigma rules, custom Falcon queries, Grafana/Loki dashboards).
• Cloud security depth in AWS or GCP (IAM, workload posture, cloud-native logging).
• Prior work in regulated environments (SOC 2, ISO 27001, PCI DSS) from the practitioner side.
• Exposure to AI/ML security concerns such as prompt injection, model evals, and data leakage through LLMs.
• Public contributions: blog posts, CVEs, open-source tools, CTF writeups.

Engagement & Logistics

• Full-time contract.
• Remote-first and async-friendly. We have hubs in San Francisco, Denver, Dublin, and Amsterdam. If you’re near one, we’d love to see you in the office regularly; if you’re elsewhere in the world, that works too.
• Potential to extend or convert based on fit.
• Reports to the Technical Operations Director; works closely with the GRC lead and IT Operations.

How We Work

We’re a lean, high-trust team. We value people who ship, who can operate independently, and who treat security as an engineering problem rather than a checklist. If you’re someone who sees a repetitive task and immediately thinks “this should be a script, or better yet, an agent,” you’ll fit in here.

To Apply

Tell us about a time you used AI, automation, or custom tooling to meaningfully change how a security workflow ran. What was manual before, what it looked like after, and what you learned. Links to code, writeups, or demos are welcome.

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 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

Tech Stack & Focus Areas

Core: C#, .NET 10

Cloud & Orchestration: Kubernetes, Helm, Docker, Azure

AI Development: Claude Code (primary), prompt engineering, AI agents & agentic workflows, LLM API integration (Anthropic, Azure OpenAI, OpenAI)

Architecture: Event-driven systems, Microservices, SOLID, platform-oriented reusable component design

Performance: Multithreading, concurrency, high-throughput distributed systems

Security: Encryption, zero-trust principles, secure coding

Quality: Unit testing, integration testing, CI/CD pipelines, automated quality tooling, intelligent observability/monitoring

Who We Are

We're an energetic and technically minded team of software builders based in Alkmaar, operating under the belief that AI-First is AI-Proof. We care deeply about engineering quality, craftsmanship, and building products that matter — and we're using AI to do it faster and better than ever before.

Our culture is grounded in three pillars: competence, craftsmanship, and trustworthiness. We work in a social, international, and inclusive environment where your ideas shape our technology. Our office is easy to reach, our culture is collaborative, and we value healthy work/life balance.

We offer competitive pay, strong benefits, and the chance to work on meaningful systems used by some of the world's largest financial institutions.

So, what’s the role all about?

We build advanced Financial Market Compliance solutions that help global banks detect, prevent, and investigate financial fraud.

We are mid-transformation — moving from individual products into a unified, AI-native compliance platform. This platform is designed to be shared, modular, and built to scale across every product line we support.

The AI features we're actively building include false-positive elimination, automated investigation workflows, and advanced compliance search — capabilities that were previously intractable and are now unlocked by AI. Engineers joining now will be core contributors to this platform from the ground up.

How will you make an impact?  

• Contribute to building our new horizontal compliance platform — designing shared components and plug-and-play modules used across every product
• Work in a cross-functional team alongside engineers, QA, architects, and product owners, spanning foundational, data engineering, and application layers of the
• Write clean, maintainable, well-tested code using Claude Code as your primary AI development tool — accelerating your output while maintaining full ownership and quality standards over everything you ship.
• Build and work with AI agents to automate development workflows, eliminate toil, and unlock capabilities that previously required manual effort.
• Design APIs, microservices, and data flows for large-scale distributed
• Share what you learn — internal tech talks, documentation, and mentoring peers across platform layers are first-class contributions here.
• Own the full lifecycle of the components you build:

Have you got what it takes?

Bachelor or Master’s degree in Computer Science (or equivalent practical experience)

• Bachelor or Master's degree in Computer Science (or equivalent practical experience)
• 4+ years of professional software engineering experience
• Strong C# / .NET development background
• Hands-on daily use of AI coding assistants (e.g. GitHub Copilot, Cursor, or Claude Code) as a core part of your development workflow — not just occasional use
• Ability to critically evaluate, verify, and improve AI-generated code — you own what gets committed, regardless of how it was produced
• Working knowledge of prompt engineering for development tasks: writing effective prompts for code generation, refactoring, test writing, and documentation
• Solid understanding of design patterns (DDD, SOLID), clean code, maintainability, and modern development practices
• Experience building distributed, cloud-native, or microservices systems
• Familiarity with Kubernetes, Helm, Docker, and cloud infrastructure (Azure)
• Understanding of multithreading, concurrency, and performance optimization
• Knowledge of secure coding, encryption, and application security
• Good English communication skills — direct, clear, and collaborative
• A positive team mindset and passion for building great software
• Collaborate through Git-based workflows, code reviews, and continuous integration practices

You will have an advantage if you also have:

• Experience with event-driven architectures (RabbitMQ, Kafka, Azure Service Bus)
• Cloud-native observability (OpenTelemetry, Prometheus, Grafana)
• Integration of LLM APIs (Azure OpenAI, Anthropic, OpenAI) into production systems
• Experience designing or working with AI agents and agentic automation workflows
• Experience evaluating and rolling out AI developer tooling across an engineering team

Our Recruitment Workflow

1. Intro conversation (preferably in person, or via Teams)
2. Technical assessment with a light technical questionnaire to confirm readiness, followed by a hands-on assessment in which you'll build a small application on the You're encouraged to use AI tools during the assessment — we're interested in how you work with AI, not without it.
3. Final conversation with senior leadership, followed by discussion of terms

What’s in it for you?

Learn more about the Benefits at NICE

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.

#LI-Hybrid

Requisition ID: 10457
Reporting into: Group Lead

Role Type: Individual Contributor

Position Overview: 

As a Senior Software Engineer, you are responsible for driving the design, development, and scalability of our Third Party Risk Management (SaaS) platform built on Laravel (PHP). You play a key role in building new features and complex product capabilities, while ensuring high standards in performance, reliability, security, and maintainability. In this role, you’ll lead by example, owning services end-to-end from development to deployment and monitoring, driving architectural discussions, and mentoring others across the team. You’ll combine hands-on development with technical leadership; contributing to architectural direction, mentoring engineers, and continuously improving engineering practices. We’re looking for someone who is not only passionate about building great software, but also excited to explore how AI can unlock faster ways of working for themselves and their teammates.

Key Responsibilities:

• Design and own secure, scalable services within our Laravel applications, guiding technical decisions and evaluating trade-offs (including AI- driven components) to meet reliability, performance, and cost goals
• Leverage AI tools to accelerate coding, debugging, testing, and prototyping, while rigorously validating outputs to ensure quality and safety
• Advise on appropriate AI use (model concepts, prompt patterns, ethical/privacy considerations), embed monitoring and compliance checks into workflows, and document residual risks and mitigations
• Coach peers on engineering best practices and AI-augmented approaches; partner with Product, Security, DevOps, and other teams to align on features, deployment, and compliance.
• Scout and pilot emerging tools or frameworks (including AI toolchains), integrate automated governance checks into pipelines, and enhance observability and incident response with an eye on productivity, cost, and resilience
• Diagnose and resolve high-impact production issues, performing root cause analysis and implementing long-term fixes
• Contribute to and guide architectural decisions and technical roadmap discussions
• Review code, uphold engineering standards, and improve testing and CI/CD practices
• Mentor and coach engineers (Software Engineer I & II), providing technical guidance and feedback
• Collaborate cross-functionally with product, design, and support teams to deliver high-impact features
• Improve observability, monitoring, and incident response processes
• Drive initiatives that improve developer experience and system health

Required Experience/Skills:

• 5-7 years of professional software engineering in an agile environment, delivering secure, scalable services.
• Deep expertise in PHP and Laravel, with experience delivering and scaling production features
• Strong experience with the TALL stack (Tailwind, Alpine.js, Laravel, Livewire)
• Advanced knowledge of relational databases (MySQL / MariaDB), including performance tuning and data modeling
• Solid understanding of frontend/backend interactions (Vue, React, or Blade)
• Solid experience with AWS or similar cloud platforms
• Understands high-level LLM concepts (e.g., hallucinations, prompt sensitivity) and safe vs. unsafe AI use cases.
• Experienced in using AI tools to accelerate coding, debugging, testing, and prototyping, with critical review of outputs
• Skilled in prompt engineering - designing reusable prompts and coaching peers
• Familiar with ethical/cost risks (bias, privacy, vendor lock-in) and embeds basic compliance checks into workflows.
• Applies security best practices in code and deployments (e.g., IAM, secrets management) and reviews AI- assisted suggestions for safety.
• Proven ability to mentor or guide peers on engineering best practices and AI-augmented workflows
• Strong experience designing scalable APIs and system integrations
• Proficiency with Docker and modern development workflows
• Experience owning features from concept to production

Your Work Environment

• A fast-growing SaaS company where you can have significant impact by building meaningful product features
• A high-ownership environment with room to shape both product and technical direction
• An inspiring office on the 13th floor of The Social Hub in Amsterdam (including gym, restaurant, and vibrant community events)

At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

AI features in JetBrains IDEs, developed by the IntelliJ AI team, have quickly become a core part of how developers work inside our IDEs. The IntelliJ AI team partners with product groups across JetBrains to embed advanced AI features that accelerate developer workflows and deliver real value to software engineers.

We are currently looking to hire a Senior Machine Learning Engineer to help us realize our ambitious vision of creating AI assistance that supports the entire development lifecycle across JetBrains IDEs. If selected, you will join the ML subteam within IntelliJ AI, driving the development of our ML system from end to end by defining evaluation and metrics, shaping context orchestration, and helping product teams tailor AI capabilities to their needs.

In this role, you will:

• Design and drive evaluation frameworks for AI features, including metrics, experiments, and agent trace analysis.
• Diagnose model performance issues (e.g. prompt drift, context mismatches, and latency/quality trade-offs) and translate findings into actionable improvements.
• Experiment with contexts and lightweight models to continuously develop our ML system.
• Act as the ML liaison for product teams across JetBrains, adapting and scaling AI capabilities in JetBrains IDEs to their needs.
• Build and maintain small helper models (e.g. re-rankers, classifiers, embedding models) to support domain-specific tasks.
• Collaborate with colleagues in ML, product, engineering, and analytic teams to deliver improvements and monitor their impact in production.
• Stay up to date with research in the fields of LLMs, agents, and evaluation, bringing best practices into our workflows.
• Mentor junior engineers and help shape team culture, processes, and tooling around experimentation and evaluation.

We’d be happy to have you on our team if you: 

• Have 5+ years of experience as an ML Engineer, with a solid background in production-grade ML systems (especially LLMs and agent architectures).
• Have experience with LLM evaluation methods and frameworks.
• Can design and run end-to-end experiments – hypotheses, metrics, data collection (including traces/logs), analysis, and decision-making.
• Are skilled in context-aware pipelines or conversational/agent systems.
• Have strong Python programming skills.
• Bring hands-on experience in fine-tuning or training smaller models (e.g. domain-specific fine-tuning and lightweight customizations).
• Communicate clearly and effectively across teams, translating ML/AI insights into product features.
• Have prior mentorship experience with ML/evaluation engineers.
• Thrive in a cross-functional, fast-moving environment, taking ownership, iterating quickly, and delivering results.

We’d be especially thrilled if you have: 

• Familiarity with agent-based systems and orchestrating multi-step reasoning agents.
• Experience with the Kotlin programming language.

#LI-MR1

About the Team

The Platform & Security team ensures Typeform engineers can build, deploy, and operate services safely and efficiently.

As we scale into AI-powered products, our engineering velocity has increased significantly. New workloads—such as model-serving, agent-based systems, and real-time data pipelines—introduce security challenges that our current team does not yet have the bandwidth or AI-specific expertise to manage.

You’ll join as a DevSecOps Engineer to embed security into the development lifecycle, enable high-velocity feature delivery, and ensure that new AI capabilities are safe, compliant, and resilient. This role is an opportunity to make a tangible impact on the security posture of Typeform as we scale.

Things you will do:

• Embed security into the SDLC: Partner with engineering and AI teams to ensure features are delivered safely at high velocity.
• Develop security automation: Build and maintain CI/CD security tooling and processes (SAST/DAST, secrets management, artifact scanning).
• Assess and mitigate risks: Conduct vulnerability assessments, threat modeling, and code reviews for platform and AI workloads.
• Advise on architecture: Recommend secure patterns for infrastructure, agent systems, and model-serving pipelines.
• Implement monitoring & incident response: Ensure timely detection and automated response to security alerts.
• Define best practices: Create and maintain standards, policies, and reusable security infrastructure components.
• Collaborate effectively: Influence teams to adopt security practices without slowing development, and act as the internal advocate for security.

What you already bring to the table:

• Several years of experience in DevSecOps, security engineering, or cloud security.
• Strong understanding of distributed systems, cloud-native infrastructure, and CI/CD pipelines.
• Knowledge of threat modeling, vulnerability assessment, and incident response.
• Experience with or strong willingness to learn AI/ML security, model-serving pipelines, or agent-based systems.
• Familiarity with IaC, Kubernetes, and cloud platforms (AWS, GCP, Azure).
• Excellent collaboration and communication skills to explain complex security concepts to non-security teams.

Extra awesome:

• Hands-on experience with AI security, model risk, or prompt injection mitigation.
• Experience in high-velocity SaaS or PLG environments.
• Contributions to open-source security tooling or frameworks.
• Implementing automated security testing in CI/CD pipelines for both code and infrastructure.