What You'll Do

At HG Insights, we run one of the most data-rich go-to-market environments in B2B SaaS. We're looking for a Senior AI GTM Automation Engineer who will sit inside our Sales Engineering and Solutions team and build the tools, integrations, and AI-powered workflows that make our Sales Engineers, Solutions Engineers, and Enterprise CSMs dramatically more effective.

This is a force-multiplier role. You'll embed with revenue teams, understand their daily jobs to be done, and turn manual, repetitive work into fast, reliable automations—so our best people spend their time on the work only humans can do.

Core Responsibilities

• Workflow discovery: Shadow and interview Sales Engineers, Solutions Engineers, and Enterprise CSMs to map their day-to-day workflows and build a prioritized automation backlog ranked by impact and effort
• Sales Engineering tools: Build data-assembly tools that pull from HG's APIs, automate technical discovery prep, and generate proof-of-concept materials—reducing manual pre-call and post-call work for SEs
• Solutions Engineering tools: Automate the generation of technical scoping docs, integration-architecture diagrams, and solution briefs; maintain a reusable library of solution templates and sandbox configurations
• Enterprise CSM automations: Build automations for account health briefs, QBR summaries, risk-detection alerts, and personalized outreach workflows using data from Vitally, Salesforce, and Slack
• AI-powered workflow engineering: Design and deploy LLM-based workflows using Claude and the Claude Agent SDK—building agents, MCP server integrations, and agentic pipelines that operate across the GTM tool stack
• Platform ownership: Maintain and evolve the internal GTM automation stack; document every tool so teams can self-serve; instrument monitoring so failures surface quickly

What We're Looking For

Experience

• 3–7 years in a technical role—software engineering, solutions engineering, RevOps engineering, or a closely related field
• Demonstrated track record of building internal tools or automations that eliminated manual work for a GTM or customer-facing team
• Hands-on experience integrating with SaaS APIs (Salesforce, Slack, HubSpot, Vitally, or similar)

Technical skills

• Expert-level user of Claude Code—you use it daily, understand its agentic capabilities, and can build production workflows with it
• Proficiency in Python and/or JavaScript/TypeScript for scripting, API integration, and automation
• Working knowledge of MCP (Model Context Protocol) servers and LLM-based agent frameworks
• Comfort with workflow automation platforms such as n8n, Zapier, or Make
• Familiarity with the GTM tool ecosystem: Salesforce, Vitally, Slack, Gong, Granola, Outreach, or equivalent

How you work

• Business mindset: You understand that tools are only valuable if people use them—you design for adoption, not just functionality
• Discovery-first: You run structured discovery sessions with non-technical stakeholders and translate fuzzy pain points into scoped, buildable solutions
• Ship fast, iterate often: You prefer a useful tool in users' hands over a perfect tool on a roadmap
• High reliability bar: If an automation breaks, the team loses trust—you build with monitoring and graceful failure in mind

Nice to have

• Experience working in or embedded with a Sales Engineering, Solutions Consulting, or Customer Success team
• Familiarity with HG Insights products and use cases—technology intelligence, installed-base data, or intent signals
• Prior experience building Claude-powered agents or working with the Anthropic API at a production level

Why HG Insights

We're the global leader in technology intelligence—the data that helps the world's best B2B sales and marketing teams find and close the right customers. This role offers an uncommon combination of technical depth and business impact: you'll define your own roadmap, work directly with the teams you're serving, and see your work reflected in real revenue outcomes.

We offer competitive compensation, equity, and a team that genuinely invests in your growth as an engineer and as a GTM thinker.

HG Insights is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Role

We are looking for a Senior Threat Researcher to join our Threat Detection Group within ThreatLabz. This is Hybrid role, reporting to a leader in ThreatLabz Team . You will track the evolving threat landscape, analysing emerging threats and identifying TTPs to develop critical detection and protection signatures. As part of our world-class research arm, you will ensure millions of global users remain protected through advanced malware research and behavioural analysis.

What you’ll do (Role Expectations)

• Analyse browser-based threats, including HTML smuggling and phishing, to develop robust protections

• Research vulnerabilities across OWASP, Web API, and LLM Top 10 to author prevention signatures

• Conduct static and dynamic malware analysis to mitigate emerging threats and C2 frameworks

• Develop complex automation tools and prototypes to integrate research findings into Zscaler products

• Contribute to the global security community by publishing in-depth threat analysis blogs and research papers

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.

• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.

• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.

• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.

• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• 2+ years of dedicated experience in Cyber Security Research with expertise in web attack and DOM/JS analysis

• Proficiency in browser security and analysing/deconstructing payloads within browser environments

• Hands-on experience with malware debugging and reverse engineering using tools like IDA, x64dbg, or Ollydbg

• Strong understanding of TCP/IP, Application layer protocols, and vulnerabilities across OWASP and LLM Top 10

• Experience with automation scripting in Python, Ruby, Go, or Shell to synthesise threat intelligence

What Will Make You Stand Out (Preferred Qualifications)

• Professional security certifications such as OSCP or specialised degrees in Computer Science or Information Technology

• Proven ability to implement AI-powered automation and leverage GenAI models for threat research

• Advanced reverse engineering experience specifically related to file-less threats and complex exploit techniques

#LI-Hybrid

#LI-RG

Position Summary:

We are looking for a Staff Software Engineer – Full Stack & AI Innovation with strong hands-on experience in TypeScript (Node.js, JavaScript), and/or Python and a passion for leveraging AI-driven code generation tools to accelerate development. You will play a critical role in operationalizing GenAI-based code generation platform. This role involves translating product specifications into structured inputs for GenAI tools, reviewing the code generated by GenAI tool, and providing feedback to product engineering team to improve quality and performance of the GenAI tool.

You will work closely with product managers, software engineers, and AI specialists to ensure that the generated code aligns with business and technical requirements. The ideal candidate is curious, adaptable, critic and eager to evaluate AI-assisted code generation tool.

Key Responsibilities:

• Develop, Analyze and structure product specifications for input into GenAI programming tools.
• Operate GenAI systems to generate code based on structured inputs.
• Perform detailed code reviews of GenAI-generated programs to ensure correctness, performance, and maintainability.
• Utilize several other AI-powered code generation tools (Cursor.ai, Windsurf, etc.) to compare and optimize GenAI tool in subject.
• Provide feedback to improve GenAI model outputs and prompt engineering strategies.
• Review and validate generated code for correctness, efficiency, and adherence to coding standards.
• Maintain documentation of input formats, code review findings, and feedback cycles.
• Stay current with advancements in GenAI programming tools and code generation technologies.
• Participate in code reviews and mentor junior developers.

Basic Qualifications:

• Bachelor’s/master’s in computer science, Engineering, or equivalent experience.
• 8 to 10 years' experience with strong expertise in at least one of the following:
• TypeScript / JavaScript (Node.js, React, Next.js, Angular, Vue.js)
• Python (Django, Flask, FastAPI/ RestAPI)
• Person must have designed, developed, and maintained scalable front-end and back-end applications using TypeScript/JavaScript/Python.
• Solid understanding of front-end technologies (HTML5, CSS3, Tailwind, Material UI or similar).
• Familiarity with GenAI tools and LLM-based code generation platforms (e.g., GitHub Copilot, CodeWhisperer, etc.).
• Experience with databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB).
• Hands-on experience with Cursor.ai and/or Windsurf (plus other AI-assisted coding tools like GitHub Copilot, Tabnine, Codeium).
• Strong understanding of software development principles and code review practices.
• Familiar with Code review tools (e.g. GitHub, GitLab, Bitbucket etc)
• Strong grasp of software design principles (OOP, SOLID, microservices).
• Excellent problem-solving, debugging, and collaboration skills.
• Excellent analytical and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications:

• Experience working with prompt engineering or structured input design for GenAI systems.
• Exposure to MLOps or AI model evaluation frameworks.
• Knowledge of software architecture and design patterns.
• Knowledge of containerization (Docker, Kubernetes).
• Exposure to serverless architecture and event-driven systems.
• Contribution to open-source or AI-driven development communities.

At NICE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you

So, what’s the role all about?

We are seeking a visionary Software Architect to serve as a technical leader for our engineering teams. In this role, you will bridge the gap between high-level strategy and hands-on execution, managing architectural subdomains within a large-scale platform. You will be responsible for guiding engineers toward correct technical paths, making high-stakes decisions, and relentlessly driving innovation and AI-first transformation across the organization.

How will you make an impact?

• Technical Leadership: Lead and influence multiple engineering teams, ensuring architectural alignment and high-quality technical decisions across subdomains.
• System Design: Architect resilient, multi-tenant cloud solutions and distributed event-driven systems that scale.
• Stakeholder Management: Collaborate with product leaders, directors, and cross-functional teams to navigate complex requirements in a multi-domain environment.
• API & Integration Strategy: Define robust API management strategies and ensure system resiliency through modern integration patterns.
• AI Integration: Evangelize and implement AI productivity tools (GitHub Copilot, Agents) and oversee the lifecycle of AI-driven applications utilizing LLMs.

Have you got what it takes?

• Total 14+ years and relevant 8+ years’ experience as Software Architect .
• Cloud Expertise: Proven track record of designing and deploying production-grade systems on AWS using a broad range of AWS native services.
• Architectural Depth: Deep experience in Multi-tenant Cloud Architecture, Event-Driven Systems, and Resiliency Patterns  
• Polyglot Mindset: A "right tool for the job" approach, with a willingness to work across various languages and frameworks in an AI-first environment.
• Communication: Exceptional ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• AI/LLM Proficiency: It will be good to have a person with practical understanding of AI project lifecycle specifically using LLMs and the use of AI agents to accelerate development

• Backend: Advanced proficiency in Java and Springboot Framework. Exposure to Node.js will be a significant plus.
• Infrastructure: Hands-on experience with AWS CloudFormation (YAML) and Infrastructure as Code.
• Data: Strong mastery of SQL required
• Big Data exposure to Apache Spark or Big Data processing will be a bonus.
• Frontend: Solid understanding of modern UI frameworks and frontend development principles.
• Tooling: Expert-level use of Jira, GitHub, GitHub Copilot, and Claude Code/other AI agents for productivity
• Testing : good exposure to automation testing and frameworks for unit testing , integration testing , e2e testing, performance testing.

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:  10835
Reporting into: Director, Engineering, CX
Role Type: Individual Contributor

What's the Role All About?

The Tech Manager is a senior technical leadership role responsible for driving the design, delivery, and quality of AI-driven and Conversational AI solutions across the NICE CXone ecosystem. With 15+ years of experience, you will lead and mentor a high-performing engineering team, bring deep expertise in AI models, AWS Knowledge Hub, and AWS Cloud, and serve as a key technical authority across cross-functional delivery teams. This role blends hands-on technical depth with strong people management, ensuring both engineering excellence and team growth.

How Will You Make an Impact?

Technical Leadership:

• Define and govern technical standards and best practices for AI and Conversational AI solution delivery.
• Provide hands-on guidance on the design and implementation of integrations using APIs, modern web technologies, and authentication standards.
• Lead the development of proofs of concept (PoCs) and production-ready solution components leveraging AWS Cloud, AWS Knowledge Hub, and AI/ML models.
• Drive prompt engineering, conversational design, and AI orchestration best practices across the team.
• Oversee testing, validation, and go-live activities to ensure solutions meet quality, performance, security, and usability standards.

People Management & Team Development:

• Lead, mentor, and develop a team of engineers — conducting performance reviews, supporting career growth, and fostering a culture of continuous learning.
• Define and uphold engineering standards, coding guidelines, and delivery frameworks across the team.
• Identify skill gaps and build team capability in emerging areas such as Generative AI, AWS services, and enterprise conversational platforms.
• Drive a collaborative, inclusive, and high-accountability team culture.

Technical Problem Solving & Quality:

• Diagnose and resolve complex technical challenges across SaaS applications, cloud environments, AI integrations, and data flows.
• Ensure all implementations meet enterprise-grade standards for quality, scalability, security, and performance.
• Produce and review key documentation including architecture specifications, test strategies, and deployment materials.

Delivery & Process Excellence:

• Drive Agile/Scrum delivery practices including sprint planning, retrospectives, and release management.
• Define and continuously improve engineering processes, documentation standards, and delivery frameworks.
• Align technical roadmap planning with business priorities and stakeholder expectations.
• Manage escalations effectively and maintain strong cross-functional collaboration with Implementation Engineers, Consultants, Project Managers, and Customer Success teams.

Collaboration & Stakeholder Engagement:

• Partner with senior stakeholders, customers, and cross-functional teams to translate business requirements into technical solutions.
• Participate in customer workshops, design reviews, and technical discussions — communicating architecture decisions and implementation strategies with clarity and confidence.
• Maintain transparent and consistent communication across all delivery teams.

Have You Got What It Takes?

Experience & Education:

• Bachelor's degree in Computer Science, Information Systems, Electrical Engineering, or equivalent work experience.
• 15+ years of professional experience in software engineering or technical delivery roles, with a focus on AI, digital channels, or bot/conversational applications preferred.
• 5+ years in a technical leadership or people management role (Engineering Manager, Tech Lead, or similar).

Technical & Architecture Skills:

• 7+ years of hands-on software development experience, with at least 2–3 years in a tech lead or architect capacity.
• Strong proficiency in modern programming languages such as Java, Python, C#, or JavaScript/TypeScript.
• Deep knowledge of AWS Cloud services and AWS Knowledge Hub; familiarity with Azure or GCP is a plus.
• Proven experience working with AI/ML models, Generative AI frameworks, and enterprise AI orchestration patterns.
• Strong expertise in:
• Web APIs, SOAP, and REST implementations
• Modern authentication standards (OAuth2, OIDC, SAML)
• Browser and web security (CORS, X-Frame Options)
• HTML/CSS and front-end fundamentals
• Prompt engineering and AI integration patterns
• Solid understanding of CI/CD pipelines, DevOps practices, and software architecture principles.
• Proficiency in databases (SQL/NoSQL) and data integration patterns.
• Strong understanding of conversational UX, AI-driven interfaces, and enterprise AI platforms.

Leadership & People Management:

• Demonstrated experience managing and growing engineering teams, including performance management and career development planning.
• Ability to define technical vision, establish engineering standards, and align team deliverables with organisational goals.
• Strong stakeholder management skills, including handling escalations and influencing at senior levels.
• Experience driving technical roadmap planning across multi-disciplinary teams.

Communication & Collaboration:

• Clear, confident written and verbal communication skills.
• Comfortable engaging with customers and senior stakeholders to articulate technical decisions, solution architecture, and delivery strategy.
• Effective leader in design reviews, sprint planning, technical discussions, and delivery execution.

Delivery & Process:

• Experience defining and improving engineering processes, documentation standards, and delivery governance.
• Strong track record of authoring and reviewing design documents, functional requirements, test strategies, and deployment guides.
• Experienced in Agile/Scrum environments with a focus on predictable, high-quality delivery.
• Willingness to work in US shift hours (5 PM – 2 AM IST).

You Will Have an Advantage If You Also Have:

• Hands-on experience with NICE CXone products or other cloud-based contact centre platforms.
• Experience with enterprise conversational AI platforms such as NICE CXone, Kore.ai, Amelia, Dialogflow, or similar.
• Exposure to Generative AI tools, LLM fine-tuning, or RAG-based architectures.

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. Office days focus on face-to-face collaboration, where teamwork and creative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10786

Reporting Into: Director , Engineering 

Role Type: People Management

So, What's the Role All About?

We are looking for a Specialist Software Architect to lead the architectural vision, design, and evolution of our AI-driven and Conversational Solutions platform. This role demands deep hands-on expertise in Python, AWS Cloud services, AWS Knowledge Hub, and multiple Knowledge Base technologies, along with proven experience designing simplified, scalable, and resilient architectures using microservices and AWS-native services.

You will play a critical role in shaping the technical foundation of our Conversational AI platform — one that handles millions of interactions per day, meets strict SLAs (99.99%), and supports zero-downtime deployments, robust disaster recovery, and enterprise-grade AI orchestration. You will be the go-to architect for proposing pragmatic, simplified designs that balance innovation with operational excellence.

How Will You Make an Impact?

Architecture & System Design:

• Own and define the end-to-end architecture of the Conversational AI and Knowledge platform, covering AI model integration layers, data stores, knowledge bases, and external integrations.
• Design enterprise-scale, cloud-native, microservices-based architectures capable of handling high concurrency, burst traffic, and real-time conversational workloads.
• Propose simplified, cost-effective architectural designs leveraging AWS-native services — avoiding over-engineering while ensuring scalability and resilience.
• Define reference architectures, architectural blueprints, and non-functional requirements (NFRs) for performance, reliability, security, and maintainability.
• Drive event-driven and asynchronous architectures using AWS-native services such as SQS, SNS, EventBridge, and Step Functions.
• Define best practices for microservices design, domain-driven design (DDD), API design (REST, async/event APIs), and AI integration patterns.
• Review and guide complex application-level designs, critical code paths, and AI pipeline architectures.

AI & Conversational Solution Architecture:

• Architect and evolve AI-driven Conversational solutions integrating large language models (LLMs), prompt engineering patterns, and enterprise AI orchestration frameworks.
• Design and implement Knowledge Base solutions using AWS Knowledge Hub, vector databases, RAG (Retrieval-Augmented Generation) architectures, and other knowledge management technologies.
• Define AI model integration strategies — including model selection, fine-tuning approaches, embedding pipelines, and response quality frameworks.
• Drive conversational UX architecture, ensuring seamless, context-aware, and low-latency interaction flows.
• Evaluate and recommend AI tooling, platforms, and frameworks aligned with business needs (e.g., AWS Bedrock, LangChain, OpenAI, Anthropic, Kore.ai, Dialogflow).
• Lead the design of multi-turn conversation management, intent resolution, and fallback handling architectures.

AWS Cloud & Microservices Architecture:

• Architect and optimise solutions using AWS services including but not limited to Lambda, API Gateway, SQS, SNS, Step Functions, DynamoDB, Aurora Serverless, S3, Bedrock, and Kendra.
• Design cost-efficient, elastic scaling strategies aligned with unpredictable conversational AI workloads.
• Lead cloud governance, environment isolation, multi-account strategy, and infrastructure-as-code (IaC) practices.
• Define CI/CD pipeline standards, DevOps practices, and containerisation approaches (Docker, Kubernetes) for AI workload deployments.
• Drive microservices decomposition strategies — identifying service boundaries, inter-service communication patterns, and data ownership models.

Scalability, Resilience & Disaster Recovery:

• Design for extreme scale — high concurrent users, high TPS, and real-time AI inferencing demands.
• Own resilience strategies including multi-AZ and multi-region architectures, active-active or active-passive DR setups, and graceful degradation mechanisms.
• Define and validate RPO/RTO goals, conduct chaos testing, and lead DR drills.
• Ensure zero-downtime deployment capabilities through blue/green, canary, and rolling deployment strategies.

Security, Compliance & Reliability:

• Embed security by design across all AI and data architecture layers — covering authentication, authorisation, data privacy, encryption, and model safety guardrails.
• Support compliance requirements (SOC2, ISO, GDPR) from an architectural standpoint, particularly around AI data handling and knowledge base access controls.
• Partner with SRE and DevOps teams on observability, logging, distributed tracing, and alerting for AI workloads.
• Define SLIs, SLOs, and capacity planning models for conversational AI services.

Technical Leadership & Collaboration:

• Act as a technical mentor and trusted advisor to senior engineers, tech leads, and implementation teams.
• Lead architecture reviews, design councils, and technical decision forums — championing simplicity, pragmatism, and long-term maintainability.
• Partner closely with Product Management, AI/ML teams, and delivery teams to balance innovation with execution feasibility.
• Drive the long-term AI architecture roadmap and proactively reduce technical debt.

Have You Got What It Takes?

Experience & Education:

• Bachelor's degree in Computer Science, Information Systems, Electrical Engineering, or equivalent work experience.
• 10+ years of professional software engineering experience, with at least 4–5 years in a software architect or principal engineer role.
• Demonstrated experience designing and delivering AI-driven or Conversational AI platforms at enterprise scale.

Technical Expertise:

• Deep hands-on experience with Python — including AI/ML libraries, API development, and automation scripting.
• Strong expertise in AWS Cloud services — particularly those relevant to AI workloads: Bedrock, Kendra, Lambda, API Gateway, SQS, SNS, Step Functions, DynamoDB, S3, and Aurora Serverless.
• Hands-on experience with AWS Knowledge Hub and multiple Knowledge Base technologies including vector databases, document stores, and semantic search platforms.
• Proven experience designing microservices architectures — including service decomposition, inter-service communication (REST, gRPC, event-driven), and distributed data management.
• Strong understanding of:
• RAG (Retrieval-Augmented Generation) architectures and embedding pipelines
• Prompt engineering and LLM integration patterns
• Modern authentication standards (OAuth2, OIDC, SAML)
• Web APIs — REST and async/event API design
• Databases (SQL/NoSQL) and data integration patterns
• Experience with CI/CD pipelines, DevOps practices, and containerisation (Docker, Kubernetes).
• Familiarity with AI tooling and platforms such as AWS Bedrock, LangChain, OpenAI, Anthropic, Dialogflow, or Kore.ai.
• Experience with GenAI and Agentic AI application development.

Architecture & Scale:

• Demonstrated success designing systems for high traffic, low latency, and high availability at global scale.
• Deep experience with resilience, disaster recovery, and failover design in cloud-native environments.
• Strong track record of proposing simplified, pragmatic architectural solutions that avoid unnecessary complexity.
• Experience with event-driven systems, message queues, and streaming architectures.
• Strong understanding of cloud networking, caching strategies, and data modelling for AI workloads.

Good to Have:

• Experience with CCaaS or real-time communication platforms (e.g., NICE CXone).
• Exposure to multi-region SaaS deployments and hybrid serverless/container architectures.
• Familiarity with OpenSearch or Elasticsearch for conversational data search and analytics.
• Experience with cost optimisation strategies at scale on AWS.
• Knowledge of frontend technologies (JavaScript/TypeScript, React) for full-stack architecture awareness.

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. Office days focus on face-to-face collaboration where teamwork and creative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. 

Requisition ID: 10787

Reporting Into: Director , Engineering

Role Type: Individual Contributor 

The Role

Lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

The Role

The Senior Data Scientist will lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

About HG Insights

HG Insights is the pioneer of Revenue Growth Intelligence. For more than a decade, we have delivered comprehensive, AI-driven datasets on B2B buyers, technology adoption, IT spend, and buyer intent, sourced from billions of data points. Today, we are a trusted partner to Fortune 500 technology companies, hyperscalers, and innovative B2B vendors seeking precise go-to-market analytics and decision-making.

Through an evolving suite of AI agents that incorporate first-party data and buyer signals, HG Insights enables AI-powered GTM automation across sales, marketing, RevOps, and data analytics teams, modernizing GTM execution from strategy through activation.

Role Overview

The Applied Data Scientist - Research is a collaborative analytical partner to the Head of Data Science, contributing to the design and validation of GTM insights that power the Contextual Intelligence initiative.

You will co-develop insight logic, selecting signals, designing scoring frameworks, prototyping models in Python, and validating outputs. You will also contribute to the production-ready briefs that are implemented in the data production pipeline by the engineering team.

This role sits at the intersection of statistical modeling, structured data analysis, and applied AI. You are comfortable reasoning about how to measure something rigorously, how entities and relationships in a knowledge graph can be leveraged, and how to use LLMs as a practical tool in the insight development workflow, not as a subject of research, but as part of the toolkit.

What You Will Do

Insight & Model Development

• Co-develop scoring frameworks and metrics models, contributing to signal selection, weighting logic, and model structure across a range of GTM insight types (acquisition,expansion, retention, strategic)
• Prototype insight logic in Python notebooks: assembling features from HG's structured data assets, implementing model components, and stress-testing outputs.
• Design and run validation experiments to confirm that insight outputs are directionally correct, well-calibrated, and meaningful across the full vendor universe
• Contribute to ontology and entity design, thinking through how vendors, products, companies, and relationships should be structured to support a given insight, informed by a conceptual understanding of the knowledge graph schema

Production Brief Development

• Translate insight designs into clear, implementation-ready production briefs 
• Document model specifications precisely: component definitions, feature engineering, aggregation logic, edge case handling, and expected output distributions
• Participate in handoff reviews with the production function, answering implementation questions and refining specs based on feasibility feedback

Insight Research & Discovery

• Contribute to the prioritized insights catalog, researching new insight ideas, assessing data availability, and framing feasibility
• Stay current on GTM data science approaches, competitive intelligence methodologies, and relevant analytical techniques that could expand the insight library

What We're Looking For

Core Skills

• Statistical modeling depth: Ability to design and implement a range of scoring and metrics models from first principles; comfortable with component weighting, normalization, signed rate-of-change metrics, composite aggregation, and distribution analysis; knows when a technique is appropriate and why 
• Python for analytical prototyping: Strong notebook-based Python for data manipulation, feature construction, model prototyping, and output validation; pandas, NumPy, and Scikit are daily 
• SQL: Proficient in querying structured data at scale; used for signal extraction, feature derivation, and validation checks across large vendor and company datasets
• Analytical rigor & validation thinking: Ability to critically evaluate whether a model is measuring what it claims to measure; designs validation experiments, checks edge cases, and flags when outputs don't pass a sanity check
• Clear technical communication: Able to translate analytical logic into precise written specifications; the production brief is a key deliverable 

Applied AI & Graph Literacy

• LLM API usage: Hands-on experience using Claude, GPT, or equivalent APIs as a practical tool; can design effective prompts, integrate LLM steps into an analytical workflow, and evaluate output quality critically
• Knowledge graph concepts: Conceptual understanding of how entities, relationships, and properties are structured in a graph; able to reason about how graph-derived features (e.g., vendor-product-company traversals) should inform insight design, without necessarily writing production Cypher 

Nice to Have

• GTM/Management Consulting, or IT Research experience, familiarity with concepts like install base, intent signals, competitive intelligence, and market analysis. Experience writing Cypher or querying graph-structured data directly
• Experience working collaboratively with engineering, product and GTM teams
• Experience in a B2B SaaS or data products environment

Tools & Environment

Primary

• Python (pandas, NumPy, scipy, Jupyter)
• SQL
• LLM APIs (Claude, GPT)
• Git and version control

Working Knowledge

• Databricks
• Cloud storage 
• Knowledge graph concepts 

Overview:

We are seeking a highly experienced Platform Engineer to architect, build, and operate a next-generation AI-powered Internal Developer Platform (IDP) that enables rapid, secure, and scalable software delivery across the enterprise.

This role will manage a critical Kubernetes platform and drive automation through Terraform, ArgoCD, and Azure DevOps. While your foundation is rooted in SRE and DevOps excellence, you will also lead our efforts to integrate Agentic AI into the platform, building intelligent workflows that automate environment provisioning, incident triage, and self-service capabilities to eliminate operational friction.

You will operate at the intersection of Platform Engineering, Cloud Infrastructure, AI automation, and Developer Experience, building systems that empower engineering teams to move faster with higher reliability and lower operational overhead.

Tech Stack Mandate

What You’ll Do: 

• Platform Architecture: Design, Develop and evolve a self-service Internal Developer Platform (leveraging Backstage or similar) to abstract cloud complexity for engineering teams.
• Infrastructure as Code (IaC): Lead the development of modular, enterprise-grade Terraform libraries to manage multi-region Azure and AWS environments.
• Kubernetes Orchestration: Operate and manage large-scale Kubernetes clusters, focusing on networking, security hardening, and workload autoscaling.
• Continuous Delivery: Own the CI/CD lifecycle by building robust Azure DevOps Pipelines and implementing GitOps patterns using Argo CD.
• AI-Enhanced Automation: Develop Python-based automation and AI agents to assist in infrastructure scaffolding, policy enforcement, CI/CD actions and proactive cost optimization.
• SRE & Reliability: Partner with dev teams to define SLIs/SLOs and integrate observability (Datadog/Prometheus) to create self-healing infrastructure loops.
• Developer Advocacy: Continuously improve Developer Experience (DevEx) by reducing cognitive load and providing automated onboarding and documentation for new services.

Required Technical Qualifications: 

• 7+ years in Platform Engineering, DevOps, or Site Reliability Engineering.
• Expert-level Terraform: Experience managing complex state, custom providers, and enterprise-grade modules.
• K8s Specialist: Deep understanding of CNI, CSI, Ingress Controllers, and Service Mesh.
• Python Mastery: Ability to write production-grade Python for building CLI tools, automation scripts, and AI agent logic.
• Agentic AI Experience: Proven experience moving beyond simple prompts to building autonomous agents that use tools/APIs to perform tasks day to day platform engineering tasks
• Production GitOps: Hands-on experience scaling Argo CD across hundreds of microservices.

Preferred Qualifications: 

• Experience with Azure OpenAI Service and building RAG (Retrieval Augmented Generation) systems f
• Knowledge of Policy-as-Code (OPA/Gatekeeper or Kyverno) integrated into CI/CD.
• Background in FinOps, specifically using AI to drive automated cloud cost reduction.

Competencies:

• Zero-Touch Provisioning: A developer can go from "Idea" to "Production-Ready URL" in minutes via an AI-guided workflow.
• Autonomous SRE: AI agents proactively identify and fix 30% of common infrastructure drift or pod failures before a human is paged.
• Immutable Infrastructure: 100% of production changes are driven via Terraform and Argo CD—no manual "click-ops."

What We Offer: 

• Competitive compensation 
• Employee medical coverage 
• Central office location 
• Entrepreneurial environment, autonomy, and fast decisions 
• Casual work environment 

About Guidepoint: 

Guidepoint is a leading research enablement platform designed to advance understanding and empower our clients’ decision-making process. Powered by innovative technology, real-time data, and hard-to-source expertise, we help our clients to turn answers into action. 

Backed by a network of nearly 1.75 million experts and Guidepoint’s 1,600 employees worldwide, we inform leading organizations’ research by delivering on-demand intelligence and research on request. With Guidepoint, companies and investors can better navigate the abundance of information available today, making it both more useful and more powerful. 

At Guidepoint, our success relies on the diversity of our employees, advisors, and client base, which allows us to create connections that offer a wealth of perspectives. We are committed to upholding policies that contribute to an equitable and welcoming environment for our community, regardless of background, identity, or experience. 

#LI-AD2

#LI-HYBRID

About the Role

NICE is seeking a talented AI Engineer to accelerate innovation across the APAC region by leading AI-centric Proof of Concepts (POCs) and Pilots alongside our extended solution and sales engineering teams. This role sits at the intersection of cutting-edge AI development and customer-facing technical delivery, with a special focus on Agentic AI solutions that push the boundaries of what is possible with intelligent automation and large language models.

The AI Engineer will work hands-on to design, build, and demonstrate AI-powered solutions, translating complex technical capabilities into tangible business value for customers across APAC.

How will you make an impact?

Agentic AI POCs & Pilots

• Design and build Agentic AI proofs of concept

     Architect and develop end-to-end Agentic AI solutions demonstrating autonomous decision-making, multi-step reasoning, and task orchestration across APAC customer engagements.

• Prototype rapidly

     Build lightweight, demonstrable prototypes using LLMs, agent frameworks, and NICE /Cognigy platform APIs to showcase the art of the possible.

Development & Engineering

• Develop and integrate APIs, webhooks, and microservices connecting LLMs and AI models to enterprise platforms and CX workflows.
• Build and maintain reusable AI accelerator assets, code templates, and demo environments for the extended APAC team.
• Implement prompt engineering strategies, RAG pipelines, and agent orchestration frameworks LLM & AI Model Expertise
• Apply knowledge of large language models (GPT-4, Claude, Gemini, Llama, etc.) to design appropriate solutions for customer use cases.
• Evaluate and select the right model, fine-tuning approach, or retrieval strategy for each POC based on accuracy, latency, and cost requirements.
• Stay current with the rapidly evolving LLM ecosystem including model releases, agent frameworks, and emerging AI tooling.

Collaboration & Knowledge Sharing

• Contribute to internal playbooks, documentation, and demo libraries to uplift the broader team’s AI capabilities.
• Engage with customers directly to understand requirements and translate them into practical AI solution designs.

Have you got what it takes?

• Bachelor’s degree in computer science, Software Engineering, or a related field or equivalent experience.
• 4-8 years of software development experience in developing high performance, highly available and scalable enterprise-grade software products that can perform, scale, and integrate into a broad enterprise ecosystem.

Programming proficiency:

.

• Experience with REST APIs, JSON, cloud SDKs
• Familiarity with data processing, vector databases and embedding pipelines for RAG architecture.
• Ability to debug, iterate quickly, and deliver working demos under tight timelines.

AI & Machine Learning Understanding

• Solid conceptual and practical understanding of machine learning fundamentals, NLP/NLU, and generative AI.
• Experience designing or building Agentic AI systems — including tool use, memory, planning, and multi-agent coordination.
• Understanding of responsible AI practices, hallucination mitigation, and evaluation methodologies for LLM outputs.

LLM Usage & Prompt Engineering

• Proficient with LLM APIs     including OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, and open-source models via Hugging Face or Ollama.
• Strong prompt engineering skills: few-shot prompting, chain-of-thought, structured outputs, and system prompt design.

Version Control & Collaboration Tools

• GitHub / Git proficiency:

     Comfortable with branching strategies, pull requests, code reviews, and collaborative development workflows.

• Ability to manage, share, and version AI demo assets and code in shared repositories accessible to the extended team.
• Experience with CI/CD basics and familiarity with tools such as GitHub Actions, or similar pipelines, is advantageous.

.

You will have an advantage if you also have:

• Experience with NICE CXone, Cognigy (conversational AI & agent orchestration platform), or similar CCaaS / conversational AI platforms.
• Knowledge of the APAC technology landscape and experience working with enterprise customers in the region.
• Background in contact centre, CX, or enterprise SaaS environments.
• Exposure to voice AI, speech-to-text/text-to-speech pipelines, or real-time AI in contact Centre contexts.

What’s in it for You?

Join an ever-growing, market-disrupting, global company where 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 about AI, innovative at heart, and excited to constantly raise the bar on what intelligent technology can do, 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: 10692                

Reporting into: Director,Solution Engineering

Position Summary:

We are seeking a Solution Architect – (AI Infrastructure & Hybrid Cloud) to lead the strategic design, architecture, and deployment of large-scale, enterprise-grade Red Hat OpenShift and Kubernetes environments. As a technical authority at the L4 level, you will be responsible for defining the blueprint of our cloud-native infrastructure, ensuring it is secure, scalable, and highly automated.
The ideal candidate acts as the bridge between traditional infrastructure and modern DevOps, serving as the lead design authority for global clients. You will collaborate with Network and Firewall Architects to build a unified fabric where containerized workloads, legacy data centers, and hybrid cloud environments coexist seamlessly through advanced automation and Infrastructure-as-Code (IaC).

Key Responsibilities:

• Architect and Design Enterprise OpenShift Solutions: Lead the high-level design (HLD) and low-level design (LLD) for multi-tenant Red Hat OpenShift and Kubernetes clusters across on-prem and hybrid cloud environments.
• Define the technology stack, standards, and blueprints for deploying AI solutions across global, multi-region public clouds (AWS/Azure/GCP) and diverse on-premise hardware.
• Oversee the successful end-to-end rollout of critical services including AI SOC, OpenShift AI, and AI-based Cybersecurity Log Optimization.
• Drive Network DevOps Strategy: Define and standardize the automation roadmap using Ansible, Terraform, and Python to achieve "Zero-Touch" infrastructure provisioning and configuration.
• Lead Customer & Stakeholder Engagement: Act as the primary technical consultant for global clients, leading design workshops, architecture validation, and executive-level technical reviews.
• Integrate Advanced AI apps, Networking & Security: Collaborate with Pre-sales, AI application developers & Engineers, Firewall Architects to design secure AI agents & use cases, container networking (CNI) models, implementing Zero-Trust security, service mesh (Istio), and micro-segmentation within OpenShift environment.
• Optimize Hybrid Infrastructure: Oversee the seamless integration of OpenShift with physical networking (Cisco ACI, VXLAN) and virtualized platforms (RHEL-V, VMware ESXi).
• GPU & Hardware Orchestration: Design and manage hardware acceleration using the NVIDIA GPU Operator and Node Feature Discovery (NFD). Implement Multi-Instance GPU (MIG) and time-slicing to optimize resource utilization across multi-tenant clusters.
• Establish CI/CD Governance: Architect robust CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions) for infrastructure and application delivery, ensuring compliance and security are baked into the workflow.
• Lead Observability & Reliability: Design comprehensive monitoring and logging architectures using Prometheus, Grafana, and ELK stack to ensure 99.99% availability of cluster services.
• Mentorship & Technical Leadership: Guide and mentor L2/L3 engineers, providing expert-level escalation support and establishing best practices for the DevOps and Network teams.
• Innovation & R&D: Evaluate and introduce emerging technologies such as Advanced Cluster Management (ACM), Advanced Cluster Security (ACS), and Cloud-Native Networking (OVN-Kubernetes).

Basic Qualifications:

• Bachelor’s or master’s degree in computer science, Engineering, or a related field
• 10+ years of progressive experience in systems architecture, infrastructure engineering, or network DevOps.
• Expert/Architect-level proficiency in OpenShift (RHOS), and Kubernetes architecture in large-scale production environments.
• Experience architecting hybrid-cloud OpenShift solutions involving AWS (ROSA), Azure (ARO), or Google Cloud.
• Proven track record in Automation & IaC: Mastery of Ansible, Terraform, and Git-based workflows to manage complex infrastructures.
• Deep understanding of Linux (RHEL) Internals: Mastery of kernel networking, storage drivers (CSI), and container runtimes (CRI-O).
• Strong Network Background: In-depth knowledge of BGP, VXLAN, and EVPN as they apply to connecting containerized workloads to physical data center fabrics.
• Experience in "Architecture as Code": Ability to develop and maintain compliance artifacts, design validation reports, and automated documentation.
• Excellent Leadership Skills: Demonstrated ability to manage high-stakes customer relationships and lead cross-functional technical teams

Preferred Qualifications:

• Certifications: Red Hat Certified Architect (RHCA), Red Hat Certified Specialist in OpenShift (Administration/Development), or CKA/CKS (Certified Kubernetes Administrator/Security), AWS/GCP Certified DevOps Engineer, AWS Certified SysOps Administrator, HashiCorp Certified: Terraform Associate
• Red Hat Certified OpenShift Administrator, AWS Certified AI Practitioner, Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP)
• Security Focus: Exposure to DevSecOps tools (e.g., Quay, StackRox) and zero-trust framework implementation
• Legacy Integration: Familiarity with Cisco ACI, Arista CloudVision, or Juniper Apstra for end-to-end automation integration
• Red Hat OpenShift AI (ROAI) expertise will be preferred
• Familiarity with LLM deployment requirements and vector database infrastructure
• Background in Cybersecurity infrastructure (SIEM, SOAR, SOC & VAPT platforms)
• Experience with MLOps infrastructure (Kubeflow, MLflow) and high-speed telemetry pipelines

What’s the role?

You will design and build automation frameworks and AI-enabled testing capabilities used across multiple teams. This role focuses on engineering scalable systems and tools, not just writing tests—turning real-world workflows into reusable automation and intelligent validation.

How will you make an impact?

• Design, develop, and maintain shared automation frameworks and platform components used across teams.
• Build and extend AI-enabled automation solutions, including intelligent validation and test generation.
• Develop service-level and API automation, ensuring coverage across distributed systems.
• Integrate automation into CI/CD pipelines, enabling continuous validation at scale.
• Collaborate with architects and engineering teams on backlog-driven platform development.
• Improve automation efficiency through AI-assisted development, test generation, and analysis.
• Debug and diagnose issues across automation, services, and system interactions.

Have you got what it takes?

• 5–8 years of professional software development experience (not just test execution).
• Strong programming skills in Java or C# with solid object-oriented design principles.
• Hands-on experience with modern automation frameworks (Playwright or similar).
• Experience building API and service-level automation (REST or event-driven systems).
• Working knowledge of Python, especially for AI-related workflows or tooling.
• Experience integrating automation into CI/CD pipelines.
• Strong understanding of system design, debugging, and maintainability.
• Ability to work across teams and contribute to shared platforms and frameworks.

AI & Automation expectations

• Hands-on exposure to LLMs or AI-assisted development tools.
• Experience applying AI/LLM tools to automate test generation, validation, or analysis.
• Practical mindset for using AI to solve real engineering problems, not just prompt tuning.

Nice to have

• Experience with TypeScript-based frameworks (Playwright ecosystem).
• Familiarity with cloud platforms (AWS/Azure).
• Experience building internal tools, SDKs, or shared libraries.
• Exposure to observability and debugging tools.
• Experience working in distributed systems or microservices environments.

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.

Req ID: 10559
Reporting into: Tech Manager, Engineering, CX
Role Type: Individual Contributor

Role Overview:

We are looking for a hands-on Product Architect / Engineer to design and build an AI-driven operations platform focused on intelligent automation, insights, and optimization across cloud, network, and application operations.This role blends product thinking, architecture, and deep engineering across AI/ML and Agentic AI systems.

Key Responsibilities:

• Architect and build the agentic AI platform leveraging AI, ML, and Agentic AI frameworks
• Design multi-agent systems for use cases for operations domains like Cloud Ops, NetworkOps, ServiceDesk, root cause analysis, anomaly detection, and predictive insights
• Develop data pipelines and telemetry fabric for ingesting and processing large-scale operational data (logs, metrics, traces, topology)
• Build and integrate LLM-powered copilots and autonomous agents for operations 
• Define product architecture, including microservices, APIs, event-driven systems, and scalable cloud-native patterns
• Translate business needs into AI-driven product features and accelerators
• Collaborate with product, operations, and engineering teams to deliver end-to-end capabilities

Key Skills:

• Strong experience in product architecture and full-stack engineering
• Hands-on expertise in:
• AI/ML (model development, inference, MLOps)
• LLMs and Agentic AI frameworks (multi-agent orchestration, reasoning systems)
• Data engineering (streaming, batch, real-time analytics)
• Proficiency in Python and modern frameworks
• Experience with cloud platforms (AWS, Azure) and cloud-native architecture
• Agent framework experience – Microsoft agent framework, langgraph and langchain.
• Strong understanding of:
• Observability systems (logs, metrics, traces)
• AIOps / IT operations platforms
• API design and microservices architecture
• Familiarity with vector databases, embeddings, RAG architectures, and knowledge graphs

Good to Have:

• Experience building autonomous AI agents for IT/network/application operations
• Exposure to FinOps, Cloud Cost Optimization,
• Knowledge of network topology, infrastructure ops, or ITSM tools
• Experience with real-time decisioning systems and event correlation engines

About the Role

We are looking for a Senior Staff Software Engineer to join the Veeam Data Cloud (VDC) engineering team at its highest individual contributor tier. In this role, you will shape the long-term technical direction of VDC, operating with organization-wide scope and influence. You will define architectural standards, resolve the most complex and ambiguous engineering challenges, and mentor a generation of Staff and senior engineers.

This is a rare opportunity to be a founding technical voice on greenfield projects — designing next-generation data protection services that will be deployed and relied upon worldwide. You will be a trusted partner to engineering leadership, product management, and cross-functional stakeholders, bridging technical excellence with business strategy.

What You’ll Do

• Technical Strategy & Architecture

  • Own and drive the multi-year technical roadmap for the Veeam Data Cloud platform, aligning engineering decisions with company strategy.
  • Define, communicate, and enforce architectural standards, design patterns, and engineering principles across multiple teams and product areas.
  • Lead architectural reviews for major systems, proactively identifying structural risks and establishing long-term scalability and resilience frameworks.
  • Author foundational technical design documents (RFCs, ADRs) that serve as the engineering blueprint for the broader organization.

  Engineering Execution & Excellence

  • Personally contribute to the most critical, highest-complexity engineering challenges across the organization — including those that span team boundaries.
  • Design and develop highly reliable, planet-scale SaaS microservices integrated with managed cloud services (Azure, AWS, GCP) using Golang and modern cloud-native patterns.
  • Establish and champion engineering quality standards: testing philosophy, observability, performance benchmarks, security posture, and release reliability.
  • Drive the adoption of emerging engineering practices — including AI-powered developer tooling, automated code generation, and LLM-assisted testing and debugging.

  Organizational Leadership & Influence

  • Serve as the primary technical escalation point across engineering — resolving the most ambiguous, cross-cutting problems that no individual team can own alone.
  • Partner with engineering managers and directors to set execution standards, unblock delivery, and ensure timely, predictable outcomes across multiple teams.
  • Represent engineering in cross-functional leadership forums (product, security, infrastructure, finance) and act as a decision-maker on technical trade-offs with business impact.
  • Drive the organization-wide engineering culture: nurturing psychological safety, technical curiosity, and a bias toward measurable outcomes.

  Mentorship & Talent Development

  • Provide deep technical mentorship to Staff, Senior, and mid-level engineers, accelerating their growth and expanding team capability.
  • Lead structured technical coaching, design review sessions, and architectural war-games to sharpen engineering judgment across the organization.
  • Identify, recruit, and help retain top engineering talent; actively shape the interview process and hiring bar for senior roles.

  Operational Ownership

  • Participate in on-call rotation and lead incident response for critical production events, driving root cause analysis and systematic resolution.
  • Own post-incident reviews and embed learnings into platform improvements and operational runbooks.

What You’ll Bring

• 15+ years of progressive software engineering experience, with a proven track record as a principal-level individual contributor.
• Demonstrated expertise designing, building, and operating SaaS or large-scale cloud services on Azure, AWS, or GCP at organization-defining scale.
• Deep expertise in Go (Golang) and/or other systems-grade modern languages (C#, Java, Rust, Scala); polyglot mindset with language-agnostic design thinking.
• Mastery of distributed systems: event-driven architecture, eventual consistency, high-availability design, and fault-tolerant microservices.
• Expert-level command of container orchestration (Kubernetes, Docker) and cloud-native infrastructure patterns.
• Exceptional communication and leadership skills — able to drive clarity and alignment across engineering, product, and executive audiences.
• Strong computer science fundamentals: data structures, algorithms, concurrency, and systems design.
• A track record of delivering greenfield projects from zero to production at scale, with full ownership of quality, security, and reliability.

Bonus Skills

• Experience leveraging AI capabilities (LLMs, generative AI, co-pilot tooling) in product development workflows — either as a feature builder or as a force-multiplier for engineering productivity. 
• Hands-on experience building AI-powered features into SaaS products: integrating model APIs, designing prompt pipelines, or building AI-assisted developer experiences.
• Background in data protection, backup, disaster recovery, or storage infrastructure.
• Experience in platform or infrastructure engineering serving other engineering teams as internal customers.

What You’ll Get

• 18 paid vacation days, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
• Private medical coverage for you and up to four dependents
• Life, accident, and disability insurance with enhanced coverage
• Annual flexible wellbeing allowance for physical and mental wellness
• Free confidential counselling and coaching via Employee Assistance Program (EAP), including legal and financial advice
• Meal, fuel, and transportation benefits based on work arrangement
• Daycare reimbursement and safe cab facility for eligible employees
• Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning

Please note: If the applicant is permanently located outside India, Veeam reserves the right to decline the application. 

#LI-KP1

Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

The Role

We are looking for an elite engineer who builds like a hacker and communicates like a consultant. You will not just be building models in a notebook; you will be deployed to the front lines to build, architect, and ship end-to-end Agentic AI products directly for our most strategic customers.

This is a high-stakes role. You will face "tricky" customers who have vague requirements and high expectations. Your job is to translate their chaos into technical order, write production-grade code, and deploy autonomous agents that solve their actual business problems.

What You Will Do

• Build & Deploy (60%):

Design and ship full-stack AI applications. You own the pipeline from data ingestion to the LLM inference layer to the frontend interface.

Architect autonomous agentic workflows (using frameworks like LangChain, LangGraph, or custom implementations) that can reason, plan, and execute complex tasks.

Write robust, clean, and highly testable code (Python/Typescript). "It works on my machine" is not acceptable; it must work in the customer's restricted cloud environment.

Handle DevOps and MLOps constraints: Dockerizing agents, managing Kubernetes clusters, and optimizing inference latency.

• Customer Engineering (40%):

Serve as the technical face of the company for our most demanding accounts.

Navigate complex stakeholder environments. You will push back on unrealistic demands, clarify ambiguous requirements, and steer "tricky" customers toward technically feasible solutions without breaking rapport.

Translate technical constraints into business value for non-technical executives.

Generate high-quality data for our customers and ability to review the data generated by other experts. This is one of the most critical aspects of the role.

The "Must-Haves"

• Experience: 8–12 years of total engineering experience. You started as a strong Software Engineer and evolved into an AI specialist.
• Education: B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution (IIT, MIT, Stanford, Harvard, Berkeley, CMU, or similar global top-ranking universities).
• Deep AI Fluency: You aren't just calling APIs. You understand RAG implementation nuances, vector database optimization, fine-tuning (LoRA/PEFT), and the architecture of agentic loops.
• Production Engineering: Experience with end-to-end deployment (AWS/GCP/Azure, CI/CD pipelines, Terraform, Docker).

The "Why You" (Soft Skills)

• Thick Skin & High EQ: You don't get flustered when a customer changes their mind for the third time in a week. You can hold your ground with a CTO and explain "why not" to a CEO.
• Extreme Attention to Detail: You catch the edge cases that others miss. You obsess over error handling, retry logic in agents, and data privacy.
• Grit: You enjoy the "messy" work of integrating legacy enterprise data just as much as prompting the latest model.

What will set you apart

• Public Code: A visible GitHub footprint is very helpful. We want to see your side projects, your contributions to open source, or your experiments with LLMs. Please include your GitHub link in your application.

Tech Stack

• Languages: Python (Expert).
• AI/Data (Expertise in all is not required): PyTorch, LangChain, LlamaIndex, Pinecone/Weaviate, OpenAI/Anthropic APIs, HuggingFace.
• Infra (Expertise in all is not required): Kubernetes, Terraform, AWS/GCP.

The Role

We are currently seeking a Senior Software Engineer, Backend to join the AI Platform team, which powers intelligent experiences across our AI products.

As a Senior Software Engineer, you’ll design, build, and ship services across a distributed microservices platform that supports capabilities such as document extraction, portfolio chat, and semantic retrieval capabilities. You’ll work across backend services, cloud-native data systems, async processing, and real-time streaming infrastructure, collaborating closely with frontend, product, and AI/ML engineers to deliver reliable and scalable backend systems.

This role is ideal for an engineer who thrives on solving hard backend problems, writes clean and tested production code, and can own features end-to-end in a fast-moving AI product team.

Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.

What You’ll Do

• Design, build, and maintain backend services that power AI Platform products
• Develop production systems in Python or other modern backend languages and frameworks, with strong emphasis on maintainability, reliability, and performance
• Build and evolve REST APIs and/or gRPC services, including request validation, error handling, and versioning
• Design and maintain relational and/or NoSQL data models across systems such as MySQL, PostgreSQL, DynamoDB, and Redis
• Build and maintain asynchronous processing flows using queues and worker-based systems
• Work on real-time streaming features, retrieval workflows, and service communication patterns that support AI interactions
• Write strong automated tests, including unit and integration coverage, and contribute to CI-based quality gates
• Debug production issues across service boundaries using logs, metrics, and system reasoning
• Collaborate closely with frontend, product, and AI/ML teams to define API contracts and deliver end-to-end features
• Contribute to code reviews, system quality, and engineering standards across the team

Who You Are

• Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)
• At least five years of professional backend software engineering experience in production environments
• Strong proficiency in at least one production backend language such as Python, Go OR Java and the ability to work effectively across a polyglot environment
• Strong software engineering fundamentals, including system design, debugging, code quality, testing, and operational ownership.
• Experience building and maintaining REST APIs and/or gRPC services
• Experience with relational databases and/or NoSQL data stores in production systems
• Experience with asynchronous processing patterns such as queues, workers, retries, and failure handling
• Proficiency with Docker and familiarity with modern backend development workflows
• Strong testing discipline, including unit testing, integration testing, and mocking dependencies
• Experience building or operating services on cloud infrastructure in a production context
• Strong communication and collaboration skills, with the ability to work effectively across frontend, product, and AI/ML teams
• We are looking for a strong backend software engineer, not someone whose experience is limited to scripting, framework usage, or cloud configuration without corresponding depth in production systems engineering
• Familiarity or working knowledge of AWS will be a huge plus
• [Bonus] Experience with modern backend frameworks such as FastAPI, Flask, Spring Boot, Go service frameworks, or equivalent
• [Bonus] Experience with Redis, WebSockets, or real-time streaming systems
• [Bonus] Experience with LLM/AI integration, semantic retrieval systems, or token streaming
• [Bonus] Experience with observability tooling, structured logging, or Sentry/metrics systems
• [Bonus] Experience in fintech or regulated domains

The Role

We are currently seeking a Senior Frontend Software Engineer to join the AI Platform team, Addepar’s next-generation AI platform that enables seamless insights and interaction through natural language and data intelligence across our AI products.

As a Senior Frontend Engineer, you’ll design and scale the interactive surface of AI Platform products. You’ll work at the intersection of AI, design, and systems engineering, building a class of real-time AI experiences for users — where every frame, token, and scroll behavior matters.

You will collaborate closely with product design, backend, and AI/ML engineers to deliver smooth, trustworthy AI experiences that align with Addepar’s standards of performance, transparency, and reliability.

Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.

What You’ll Do

• Design and implement complex, real-time UI features for conversational interfaces — including chat streaming, incremental rendering, and dynamic layouts.
• Build high-performance WebSocket pipelines to handle streamed deltas, retries, and backpressure gracefully.
• Optimize scrolling and rendering performance using requestAnimationFrame, virtualization, intersection observers, and non-blocking state updates.
• Implement fault-tolerant UI logic for reconnection, cancellation, offline recovery, and retry without user disruption.
• Architect state management and caching strategies to maintain consistency between local UI and backend deltas.
• Collaborate with designers to deliver accessible, responsive, and pixel-perfect interfaces across themes and viewport sizes.
• Extend Addepar’s frontend developer experience—refine the build pipeline (Vite/Webpack), test automation (Playwright, Jest), and linting/formatting standards (ESLint, Prettier).
• Instrument client-side telemetry and performance metrics to measure render latency, streaming lag, and user interaction speed.
• Mentor teammates through design reviews and pair programming, contributing to shared components and cross-product standards.
• Work closely with backend and AI/ML teams to co-design message formats, token streaming APIs, and session-level resiliency mechanisms.
• Shape the technical direction of AI Platform’s frontend, contributing to shared libraries, caching strategies.

Technical Fundamentals & Practices -

We’re looking for engineers who demonstrate mastery across the following practices and system fundamentals that empower to ship high-quality, low-latency conversational experiences at scale:

Browser & Rendering Fundamentals : 

• • Deep understanding of the browser’s rendering pipeline—DOM, CSSOM, layout, paint, compositing.
  • Ability to identify and fix layout thrashing, paint storms, and jank through Chrome DevTools performance profiling.
  • Knowledge of animation scheduling via requestAnimationFrame, idle callbacks, and microtask queues.Familiarity with modern web APIs such as IntersectionObserver, ResizeObserver, MutationObserver, OffscreenCanvas, Web Workers, and BroadcastChannel for concurrent or cross-tab coordination.

Asynchronous & Streaming Systems:

• • Strong command of Promises, async/await, generators, and cancellation (AbortController).
  • Familiarity with streaming data protocols (e.g., WebSockets, SSE) and patterns like batching, throttling, and debounce under load.
  • Understanding of backpressure and how to pace UI rendering vs. message ingress.

State & Data Synchronization:

• • Experience designing immutable data flows with fine-grained updates (diffs, patches, deltas).
  • Knowledge of caching, reconciliation, and hash-based change detection (e.g., djb2, CRC32, content hashing).
  • Practices for ensuring consistency between transient client state and authoritative backend models.

UI Architecture & Composition:

• • Familiarity with reactive component frameworks (Svelte preferred; React/Vue acceptable).
  • Experience isolating side effects, using stores/signals, and maintaining predictable reactivity graphs.
  • Ability to decompose large applications into feature modules with lazy loading, error boundaries, and shared design tokens.
  • Ability to evaluate and integrate across frameworks (Svelte, React, Web Components) while maintaining consistent patterns in state, testing, and accessibility.

Performance & Profiling:

• • Proven skill in measuring and optimizing UI latency (first paint, input delay, FPS stability).
  • Comfort with Chrome Performance, Lighthouse, or custom performance markers.Experience building virtualized views (infinite scroll, chat lists, large tables).

Design Systems & Accessibility:

• • Experience building and maintaining reusable design systems with Storybook, Tailwind, or Web Components.Knowledge of accessibility standards (WCAG, ARIA) and best practices for keyboard, color, and screen reader support.Skilled at collaborating with design teams to translate high-fidelity Figma specs into performant, production-ready components.

Resilience, Testing & Observability:

• • Writes defensive code to handle partial data, dropped connections, race conditions, and AbortErrors.
  • Understands test pyramids: unit, integration, and end-to-end (Playwright, Jest, Vitest).
  • Adds telemetry hooks and log events to diagnose production issues and user experience regressions.

Developer Experience & Tooling:

• • Comfortable configuring bundlers (Vite, Webpack) and optimizing build times.
  • Sets up linting, type checking, and pre-commit automation for consistency.
  • Experience with CI/CD, incremental testing, and feature flag rollouts.
  • Experience with AI-assisted developer tools or scripting build/test automation to improve team velocity.

Mindset:

• • You think in systems, not pages. 
  • You balance aesthetics with performance, correctness, and maintainability. You obsess over the invisible details — micro-interactions, latency, and flow — that make complex products feel effortless. 
  • You enjoy teaching others, debugging difficult issues, and making the team move faster through better abstractions.

Who You Are

• Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
• At least 5 years of professional frontend development experience in a production environment.
• Strong proficiency in TypeScript/JavaScript and deep understanding of asynchronous browser behavior.
• Experience with Svelte, React, or another component-based modern UI framework.
• Strong debugging and performance profiling skills.
• Experience integrating real-time or streaming data into user interfaces.
• Strong communication, collaboration, and mentoring skills.
• Additional certifications or licenses
• Skills and competencies that also include soft skills necessary for success
• Bonus: Familiarity with AI/LLM-powered interfaces, progressive streaming UIs, or data-rich visualization frameworks.
• You care deeply about user experience, developer productivity, and measurable performance — and you know that excellence in frontend engineering is achieved through curiosity, rigor, and empathy for both users and teammates.

ABOUT US 

Ensono is a hybrid IT services provider that sees a world in transformation. We understand the world of business has become more complex, layered, and interdependent because we’re enabling the IT infrastructure for that transformation. Our clients are some of the most innovative and forward-thinking companies in the world and we help keep their businesses thriving. With nearly 50 years of experience, we optimize and modernize IT infrastructure by amplifying the power of mainframes and mid-range servers with the agility of cloud. Check us out at www.ensono.com.

Job Summary

The Senior IT Process Analyst is responsible for designing, implementing, and operationalizing advanced AI-driven solutions to improve IT Service Management (ITSM) processes and tool efficiency. This role serves as a technical AI authority and evangelist, applying Machine Learning, Natural Language Processing (NLP), Generative AI, and predictive analytics to enhance decision-making, automation, and operational outcomes within ITSM practices.

The position focuses on translating complex operational data into explainable, scalable, and production-ready AI solutions, integrating these capabilities into enterprise ITSM tools through API-based architectures. The role supports continual process improvement by embedding AI insights into daily ITSM operations, governance forums, and performance management practices.

Duties and Responsibilities

• Design and implement AI and ML solutions to optimize ITSM processes and operational decision-making.
• Apply machine learning techniques (classification, clustering, anomaly detection) to ITSM data.
• Develop NLP models for analysis and automation of ticket, change, and knowledge data.
• Integrate Generative AI / LLM capabilities for summarization, recommendations, and content generation.
• Perform feature engineering and data preprocessing on noisy and incomplete ITSM datasets.
• Build predictive models for risk assessment, failure prediction, and trend analysis.
• Implement rules-based and AI hybrid decision models with confidence scoring.
• Monitor, evaluate, and continuously improve AI model performance in production.
• Integrate AI solutions into ITSM platforms using API-based architecture.
• Apply Explainable AI techniques to support transparency and operational trust.
• Act as an AI subject matter expert, supporting adoption, documentation, and knowledge transfer.

Qualifications & Skills

Required

• Bachelor’s Degree with 6–10 years of experience in AI, Machine Learning, Data Science, or related technical fields.
• Hands‑on expertise in Machine Learning, Natural Language Processing, and Generative AI / Large Language Models.
• Strong experience in feature engineering, predictive modeling, and data quality management.
• Proficiency in Python and SQL for analytics, model development, and ITSM data analysis.
• Experience with JSON, YAML, and JavaScript / TypeScript for API integration and service orchestration.
• Proven ability to integrate AI solutions into enterprise platforms using RESTful, API‑based architectures.
• Experience in AI model evaluation, monitoring, and continuous improvement.
• Knowledge of Explainable AI (XAI) for transparent operational decision support.

Preferred

• Experience with ServiceNow or ITSM platforms.
• Familiarity with MLOps and AI governance.
• Knowledge of ITIL-based ITSM processes.

Ensono is an equal opportunity employer and is committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or veteran status.

Responsibilities

• Analyze and comprehend requirements, create manual and automated tests, and maintain them. Execute regression test suites, analyze the test failures, and report defects.
• Identify opportunities to automate manual processes as much as possible to make release processes more efficient. Also, integrate all the touch points in the QA process, like integrating automated test results with test specs and generating reports.
• Work in an agile model. Analyze, troubleshoot and fix failures and issues in "build - test - deploy" CI/CD pipelines 
• Follow best practices in areas like security, performance and cost efficiency when working on developing the workflows
• Communicate and collaborate with a co-located and distributed team of architects, developers, QA engineers to resolve issues, and provide clear status updates 
• Escalate issues in time and able to follow up for their status 
• Works independently with minimal or no supervision, is proactive and takes ownership of the testing area 
• Ability to think out of the box 

Qualifications

• Minimum of 5-7 years of experience 
• Bachelor's degree in computer science or a related field 
• Detailed Knowledge of cloud technologies like AWS, Azure, K8S, dockers, containers etc. 
• Experience with technologies like REST APIs, Web services, NodeJS, Docker. 
• Experience using CI/CD pipeline tools like Jenkins, TeamCity. 
• Experience working on UNIX & MAC systems 
• Experience in using GIT repo, JIRA 
• Experience in Web UI and API automation (coding, scripting, etc.) and proficiency with at least one automation language, tool, or technology like Protractor, Playwright, Python etc 
• Technical expertise in Go, Yaml and Json. 
• Technical expertise in Helm. 
• Knowledge of at least one RDBMS database like Oracle, Postgresql, MS SQL Server, etc.

About Encora

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Position Overview

The Supply Chain Orchestration Knowledge Expert is a domain and subject matter expert responsible for developing, structuring, and maintaining the messaging and positioning and subsequent knowledge artifacts that power TraceLink’s Agentic Orchestration Solutions (AOS) go-to-market execution, field team enablement campaigns, and AI-driven experiences for both the customer personas and TraceLink field teams.   

Each Supply Chain Orchestration Knowledge Expert serves as the global owner of a supply chain orchestration domain—such as Manufacturing, Commerce, Logistics, or Transportation—and builds the messaging and positioning frameworks, insights, and artifacts that support executive-level conversations across all relevant customer segments.

This is a unique role combining industry analysis, supply chain orchestration, product expertise with strategic storytelling, knowledge artifact creation, and curation for executive buyer experiences.

Responsibilities

Supply Chain Orchestration Domain Expertise

• Serve as TraceLink’s subject-matter expert for a specific supply chain orchestration supporting Product Marketing, Demand Gen, Content, Sales Enablement, and Sales

• Build a deep understanding of end-to-end processes, personas, pain points, business value, and the life sciences and healthcare supply chains ecosystem.

• Participate in select cross-functional teams and executive engagements as required.

Strategic Narratives, Messaging, and Positioning

• Develop strategic narratives, messaging, and positioning of TraceLink products and solutions targeting executive personas - specifically the CIO.

• Create and maintain competitive differentiation and positioning against alternative solutions.  

• Continuously monitor the effectiveness of messaging through routine engagement with field teams, customers, and prospects.

AI and LLM Buying Experiences

• Build and maintain an LLM-ready messaging framework with modular, metadata-tagged positioning and value narratives.

• Ensure taxonomy alignment and version control so messaging remains consistent, current, and easily ingested by the LLM.

• Curate and govern the product and industry knowledge corpus to deliver accurate, compliant, and authoritative model outputs.

• Design executive-ready LLM experiences using prompt patterns, scenarios, and value-story templates for internal enablement and external buyer interactions.

Deliverables and Key Knowledge Artifacts

• Create and maintain a standard set of knowledge artifacts that inform and drive the executive interactions, field team enablement, and LLM-driven experiences, including but not limited to:

  • Domain Messaging & Positioning Playbook capturing value pillars, executive narratives, persona messaging, and competitive differentiation.

  • LLM-Ready Messaging Framework & Metadata Schema defining modular message objects, taxonomies, and canonical terminology for model ingestion.

  • Curated Knowledge Corpus Library, including process maps, capability descriptions, deal reviews, win stories, case studies, industry insights, and glossary of terms.

  • Executive Buyer Narrative Decks tailored for CIO, COO, and VP-level personas with business cases, ROI framing, and transformation stories.

  • Competitive Landscape & Differentiation Dossiers analyzing alternative solutions with scenario-based differentiation and objection-handling modules.

  • LLM Prompt Patterns, Conversation Flows, and Experience Blueprints enabling consistent, high-credibility internal and external AI-driven interactions.

  • Field Enablement Knowledge Packs providing talk tracks, use-case stories, objection handling, value frameworks, and LLM-powered microlearning assets.

Skills and Qualifications

• 3 - 5 years in a product management, product marketing, solution consulting, or analyst roles with a specific focus on life sciences manufacturing, logistics, and/or adjacent roles.

• Exceptional writing and presentation skills, especially for senior executive audiences.

• Ability to create clear, structured narratives from ambiguous or highly technical information.

• Experience producing content such as briefs, whitepapers, frameworks, or strategic analyses.

• Ability to develop insights, messaging, positioning, and competitive analyses that support commercial teams.

• Familiarity with large language models (LLMs), conversational AI, or retrieval-augmented systems.

• Experience in structuring and tagging content for AI/ML consumption is a plus.

• Ability to work cross-functionally with Product, Marketing, Sales, Solution Consulting, Value Engineering, and Services teams.

Education: Bachelor’s degree or equivalent professional experience required.

Travel: Ability to travel up to 25-40% as required by business needs.

About HG Insights

Headquartered in Santa Barbara, California, HG Insights is the global leader in technology intelligence. We help the world’s most innovative companies accelerate their go-to-market efforts with precision through advanced data science methodologies and proprietary data assets. We offer a culture that blends innovation, collaboration, and growth, where each team member is empowered to make a measurable impact.

Role Overview

We are looking for a Staff/Senior Machine Learning Engineer to join our growing AI and Data Platform team in Pune, India. In this role, you will be responsible for designing, building, and scaling ML systems that power our core data intelligence products. You’ll work at the intersection of data engineering and machine learning, collaborating closely with data scientists, software engineers, and product teams to turn models and agents into robust, production-ready systems.

This is a high-impact role suited for someone who thrives on ownership, scalability, and deploying real-world ML and AI solutions at scale.

Key Responsibilities

ML & AI System Development

• Design and build end-to-end ML pipelines, from data ingestion and feature engineering to model training, serving, and monitoring.
• Productionize AI agents, including LLM-backed workflows, multi-step tool use, and API orchestration.
• Collaborate with data scientists to bring experimental models into stable, high-performing production systems.
  
  

MLOps & Infrastructure

• Implement and maintain MLOps workflows (CI/CD for ML), tracking experiments, managing model versions, and automating retraining.
• Set up observability for models and agents, including tracing, logging, latency/error tracking, and fallback logic.
• Ensure infrastructure supports scalability, performance, and compliance requirements.
  
  

Technical Leadership & Collaboration

• Lead technical architecture for key AI and ML systems, ensuring maintainability and extensibility.
• Partner with product and platform teams to translate business needs into reliable and performant ML solutions.
• Mentor junior engineers and help elevate technical practices across the engineering org.

Minimum Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of industry experience, with at least 4+ years in ML engineering or MLOps.
• Strong programming skills in Python and experience with ML libraries such as PyTorch, TensorFlow, and scikit-learn.
• Experience deploying AI agents in production, including retrieval-augmented generation (RAG), multi-step reasoning, and tool-use orchestration.
• Familiarity with LangChain, LlamaIndex, Haystack, or similar frameworks for agent development.
• Hands-on with LLMs (OpenAI, Anthropic, Cohere, etc.), embedding models, and vector store integration.
• Expertise in MLOps tools like MLflow, Airflow, SageMaker, or Kubeflow.
• Experience with cloud platforms (preferably AWS), Docker/Kubernetes, and large-scale data systems (e.g., Snowflake, Databricks).
• Excellent problem-solving and system design skills, including CI/CD, testing, and infrastructure-as-code.
  
  

Preferred Qualifications

• Experience with streaming pipelines, online inference, and model monitoring at scale.
• Exposure to agent memory, feedback loops, or AI workflow orchestration in customer-facing products.
• Prior contributions to open-source ML or LLM projects are a plus.
  
  

Why Join HG Insights?

• Work on high-impact AI products used by global enterprise customers.
• Lead the ML engineering strategy and shape our AI platform.
• Competitive compensation and benefits tailored for India-based employees.
• A collaborative and innovation-focused team environment.
  
  

Ready to build the future of AI infrastructure? Apply now to join HG Insights as a Staff Machine Learning Engineer in Pune.

So, what’s the role all about? 

As a Senior Specialist Client Services Project Manager, you will be responsible for overseeing multiple projects and initiatives that support the organization's strategic goals. You will work closely with cross-functional teams to ensure successful project execution, on-time delivery, and adherence to quality standards. 

How will you make an impact?

Manage high‑visibility software and AI/GenAI projects, ensuring alignment with scope, timelines, and customer expectations.

Manage project plans, schedules, RAID logs, and core project documentation.

Provide consistent communication with executive leadership.

Drive ownership, accountability, and escalation management.

Guide teams through the full project lifecycle.

Mentor project managers and support PMO best‑practice maturity.

Have you got what it takes?

IT experience: 12 to 16 years

7 years of project management experience leading multiple concurrent projects in customer‑facing environments.

Proven success delivering full lifecycle projects across Agile, Waterfall, and hybrid approaches.

Experience delivering technical, SaaS, and AI/GenAI programs.

Strong analytical skills with a track record of managing risks, revenue, and escalations.

Excellent communication and expectation‑management skills.

Advanced proficiency with tools such as MS Project, Salesforce, Rocketlane, and Power BI.

PMP certification required.

AI Delivery (Preferred)

Led end‑to‑end delivery of conversational AI, LLM, and NLU solutions across scoping, execution, UAT, and deployment.

Assessed AI use cases and evaluated data readiness, including ingestion, quality, labeling, and dependency tracking.

Collaborated with engineering, product, R&D, and presales teams to validate model accuracy, output quality, and overall performance.

Set and managed customer expectations while coordinating cross‑functional delivery across technical and business teams.

Identified and mitigated AI‑specific risks such as model drift, hallucinations, data issues, and expectation misalignment.

Applied hands‑on prompt engineering with a clear understanding of prompting limitations and optimization strategies.

Leveraged AI tools in daily workflows for automation, data analysis, content generation, and quality validation.

Defined and monitored AI performance KPIs, translating metrics (e.g., accuracy, containment, hallucination rate, latency, cost per inference) into actionable insights.

Managed AI cost drivers, e.g. token usage, model selection, prompt structure, and architecture optimization for efficiency and performance.

Ensured compliance with AI safety, governance, and security standards, implementing guardrails, redaction practices, and structured evaluation frameworks.

You will have an advantage if you also have:

Experience working with Waterfall/Agile methodologies

Experience with Onsite and offshore delivery model

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: 9958

Reporting into: Tech Manager

Role Type: Individual Contributor

Performance Engineer (Senior / Specialist)

What’s the role?

You will design, execute, and evolve performance engineering practices across a distributed platform, ensuring systems scale reliably under real-world conditions. This role blends hands-on testing, system analysis, and automation, with growing use of AI-assisted tooling to improve speed and insight.

How will you make an impact?

• Design and execute performance, load, and scalability tests across services and systems.
• Analyze throughput, latency, and system behavior under realistic usage patterns.
• Identify and diagnose performance bottlenecks across application, API, and database layers.
• Collaborate with engineering teams to improve system performance and scalability early in the lifecycle.
• Build and maintain performance test suites and reusable frameworks.
• Integrate performance testing into CI/CD pipelines to enable continuous validation.
• Define and track performance baselines, SLAs (Service Level Agreements), and key metrics.
• Use AI-assisted tools to accelerate test creation, analysis, and anomaly detection.
• Contribute to best practices and standards for performance engineering across teams.
• Support production investigations and provide data-driven recommendations.

Have you got what it takes?

• 7–12 years of experience in performance testing or performance engineering.
• Strong hands-on experience with tools like JMeter, Gatling, BlazeMeter, or similar.
• Solid programming skills in Java, C#, or similar.
• Strong understanding of microservices, APIs, and distributed systems.
• Experience analyzing system performance metrics and bottlenecks.
• Familiarity with CI/CD pipelines and automated testing workflows.
• Experience with API testing and automation.
• Strong problem-solving and analytical skills.

Nice to have

• Experience with cloud environments (AWS/Azure).
• Familiarity with observability tools (Grafana, Prometheus).
• Experience with production traffic modeling and usage simulation.
• Exposure to AI/LLM-based tools for testing or analysis.

Tech stack (expected exposure)

• Performance tools: JMeter, Gatling, BlazeMeter
• Java or C#
• CI/CD tools (Jenkins or equivalent)
• Git/GitHub
• API tools (Postman or similar)
• Observability tools (Grafana or similar)
• Cloud platforms (AWS/Azure)

Req ID: 10553
Reporting into: Tech Manager, Engineering, CX 
Role Type: Individual Contributor 

So, what’s the role all about? 

Step into the role of a Software Engineer and become an integral part of our team developing the Contact Center Copilot solution. You will work on data integration, leveraging Python and AWS services to enable seamless ingestion of external system data into AWS Bedrock Knowledge Base. You’ll have the opportunity to learn, grow, and contribute to cutting-edge technologies while ensuring high-quality deliverables. 

How will you make an impact?  

• Build and maintain data pipelines for external system integration. 

• Write efficient Python scripts to automate processes. 

• Develop serverless solutions using AWS Lambda and API Gateway. 

• Collaborate with the team to integrate Salesforce and SharePoint data. 

• Assist in implementing LLM-based product enhancements. 

• Write unit tests and contribute to quality assurance processes. 

• Monitor and optimize application performance. 

• Troubleshoot and debug application issues. 

• Document technical processes and workflows. 

• Stay updated with AWS and AI advancements. 

• Support deployment processes and CI/CD pipelines. 

• Follow security best practices in code and architecture. 

• Collaborate with frontend teams for seamless backend integration. 

• Participate in Agile development processes. 

• Contribute to brainstorming sessions for new features. 

• Take ownership of assigned tasks and deliverables. 

Have you got what it takes?  

• BS in Computer Science or equivalent 

• 2-4 years of software development experience. 

• Proficient in Python programming. 

• Basic knowledge of AWS services like Lambda, API Gateway, and S3. 

• Familiarity with AWS Bedrock Knowledge Base or similar services. 

• Exposure to LLMs is an advantage. 

• Understanding of API integration with external systems like Salesforce and SharePoint. 

• Knowledge of JavaScript; Angular is a plus. 

• Strong problem-solving skills. 

• Good understanding of software development best practices. 

• Familiarity with CI/CD pipelines and version control systems. 

• Excellent teamwork and communication skills. 

• Eagerness to learn and adapt to new technologies. 

• Basic knowledge of Agile development methodologies. 

• Commitment to quality and attention to detail. 

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: 9908 
Reporting into: Tech Manager  
Role Type: Individual Contributor 

Tech Manager (Engineering) – Performance & Platform Excellence

How will you make an impact?

• Lead and grow a high-performing engineering team focused on performance, scalability, and reliability across the platform.
• Define and drive a performance engineering strategy adopted across multiple product teams.
• Manage a center of excellence, setting standards, frameworks, and governance for performance testing and scalability.
• Lead evolution of performance testing frameworks and tooling (JMeter, BlazeMeter, Gatling, or equivalent).
• Lead the development of AI-enabled testing and analysis capabilities to improve efficiency, insight, and coverage.
• Integrate performance testing into CI/CD pipelines, enabling early detection and prevention of production issues.
• Partner with architecture, product, and engineering teams to identify risks and influence system design for scale.
• Enable teams with production-like testing environments, tooling, and data strategies.
• Provide clear visibility into performance health, risks, and roadmap progress.

Have you got what it takes?

• 5+ years of experience leading engineering teams in complex, distributed environments.
• Strong hands-on background in Java or C# (.NET).
• Proven experience in performance engineering, including load, stress, and scalability testing.
• Hands-on experience with tools such as JMeter, BlazeMeter, Gatling, or similar.
• Strong understanding of distributed systems, microservices, and system bottlenecks.
• Experience integrating testing into CI/CD pipelines and release processes.
• Experience applying or experimenting with AI/LLM-based tools to improve engineering workflows.
• Ability to lead at both strategic and execution levels.

Nice to have

• Experience with cloud platforms (AWS/Azure) and containerization (Docker, Kubernetes).
• Familiarity with observability and monitoring tools (Grafana, Prometheus).
• Experience building internal platforms or shared frameworks.
• Experience driving adoption of engineering standards across teams.

Tech stack (expected exposure)

• Java or C# / .NET
• Performance tools: JMeter, BlazeMeter, Gatling
• CI/CD tooling (Jenkins or equivalent)
• Git/GitHub
• Observability tools (Grafana or similar)
• Cloud (AWS/Azure)
• Scripting (Python or similar)

Requisition ID: 10543

Reporting into: Tech Manager

Role Type: Individual Contributor

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

MAKE AN IMPACT

Job Details

Lead AI Engineer

Location: Pune (Hybrid)

Role Purpose Design and deliver AI/ML and Generative AI solutions that enhance client intelligence, automation, and decision-making across Private Banking platforms, leveraging data sourced from core banking systems (e.g. Avaloq), CRM, and digital channels.

Key Responsibilities

• Develop and deploy AI/ML and GenAI models (e.g. NLP, summarization, recommendation engines)
• Build scalable data pipelines and feature engineering workflows using structured and unstructured data
• Integrate AI capabilities into enterprise platforms via APIs and microservices.
• Work with data originating from core banking platforms (e.g. Avaloq) including client, portfolio, and transaction data.
• Enable AI-driven use cases such as client insights, next-best-action, and automation of RM workflows.
• Implement model monitoring, governance, and performance optimization aligned to enterprise standards.
• Collaborate with engineering and business teams to translate wealth use cases into scalable solutions.
• Experience working with wealth management data (clients, portfolios, transactions)
• Understanding of data flows from core banking systems such as Avaloq
• Awareness of AI governance, model risk, and regulatory considerations in banking

Skills & Experience

Primary:

• Python (mandatory) • ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) • GenAI / LLM frameworks (LangChain, OpenAI, etc.) • AWS (S3, Lambda, SageMaker, Bedrock)

Secondary: • Data engineering (ETL pipelines, feature stores) • API development • Vector databases / embeddings

About the Role

Join us as a Full Stack Staff Engineer to lead the evolution of the AlphaSense Application Portfolio through robust architecture and cutting-edge AI integration. This role is designed for a seasoned engineer who thrives on solving massive-scale frontend challenges and building performant, customer-focused systems. You will act as a strategic lead—researching and architecting solutions for complex frontends, while fostering a culture of technical excellence across the team. If you are looking to combine hands-on AI innovation with high-impact organizational leadership, this role is for you.

What You’ll Do:

• Serve as the Architectural Anchor for integrating AI into the product fabric. You will research, prototype, and deploy cutting-edge solutions using LLMs and the latest frontend technologies, ensuring these models are not just theoretical but are seamlessly integrated into high-performance, user-facing applications.
• Design the frontend architecture that serves as the gateway to our AI platform. You will build robust, scalable interfaces capable of rendering insights from millions of documents with sub-second latency. By bridging the gap between complex AI services and the end-user, you will ensure that massive-scale data is transformed into performant, intuitive, and highly responsive web applications.
• Partner with cross-functional, distributed teams to evaluate and adopt emerging technologies, while leading the seamless integration and optimization of intelligent features and high-impact workflows across the platform
• Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who you are

Core Qualifications

• 8+ years of experience building complex, data-intensive full-stack systems, with 5+ years specifically scaling production-grade services using Node.js, GraphQL, and modern JavaScript/TypeScript ecosystems.
• Deep expertise in React and TypeScript; a proven ability to codify performance best practices, navigate complex architectural trade-offs, and drive code-level improvements.
• Proven success in designing large-scale asynchronous systems using streaming, queuing, and caching strategies, supported by robust observability (logging, metrics, tracing).
• Strong proficiency with SQL/NoSQL (e.g., DynamoDB, Elasticsearch, Vespa) and cloud-native development within AWS or GCP.
• Working knowledge of Python or Java/Spring.
• Passion for AI-assisted development (e.g., Cursor, Claude) 
• Exceptional communicator able to articulate complex technical concepts and influence engineering direction across multiple teams without direct authority.
• Prior experience at global technology companies or high-growth product organizations with a high-bar engineering culture.

Nice to have

• Proficient in modern DevOps/MLOps, including CI/CD, IaC, and automated testing frameworks.
• Hands-on experience with Docker and Kubernetes for containerized application delivery.

Practical experience deploying LLM applications, agentic frameworks, or scalable AI infrastructure.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Senior Staff AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 10+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Senior Staff AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 10+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

Seeking a passionate Senior Engineer to join our Content Engineering team. This team specializes in large-scale content processing using cutting-edge technologies. In this role, you'll leverage AI applications (NLP, LLM) for document understanding, including, but not limited to, document classification, text categorization, data extraction, and semantic similarity.

Requirements:
      Must have 

• 6+ years of experience as a software engineer, primarily with Python
• Ideally, you possess an advanced degree (Bachelor's / Master's)  in Computer Science, Computer Engineering, or a relevant field with a focus on Artificial Intelligence, machine learning, but equivalent industry experience may be considered
• 2+ years of hands-on experience building and deploying applications that use Large Language Models (LLMs). 
• Experience in extracting structured JSON from text using LLMs and a deep understanding of Prompt Engineering.
• Proficiency in classic NLP libraries for tasks like NER, text classification, and pre-processing.
• Experience with LLM tracing, debugging and evaluation platforms such as Langfuse.
• Excellent communication, organizational, problem-solving, debugging, and analytical skills.

        Great to have 

• Experience in async processing of data at scale
• Using frameworks like LangChain, HuggingFace, and backend web frameworks like FastAPI.
• Expertise on core engineering skills - Cloud, microservice architecture, caching, and queuing.
• Familiarity with concepts/tools as Docker, k8s, VCS, CI/CD
• Previous experience in data extraction from specific domains (e.g., financial reports, news).
  
  

Responsibilities:

• Deploy LLM based production grade solutions.
• Fine-tune and adapt State of the art LLMs for specialized data extraction tasks. Develop innovative prompt engineering strategy and systems to maximize reliability and performance on confidential business documents.
• Solve Engineering challenges that come along with LLM solutions, such as high latency, non-deterministic output, etc.
• Implement and scale data processing pipelines that can process high volumes of complex documents with high accuracy and efficiency.
• Integrate and manage LLM Observability to trace, debug, and monitor every extraction
• Own systems end-to-end, including(but not limited to) designing, coding, monitoring, testing, CI/CD and on-call support.

About the Role:

Seeking a passionate Senior Engineer to join our Content Engineering team. This team specializes in large-scale content processing using cutting-edge technologies. In this role, you'll leverage AI applications (NLP, LLM) for document understanding, including, but not limited to, document classification, text categorization, data extraction, and semantic similarity.

Requirements:
      Must have 

• 6+ years of experience as a software engineer, primarily with Python
• Ideally, you possess an advanced degree (Bachelor's / Master's)  in Computer Science, Computer Engineering, or a relevant field with a focus on Artificial Intelligence, machine learning, but equivalent industry experience may be considered
• 2+ years of hands-on experience building and deploying applications that use Large Language Models (LLMs). 
• Experience in extracting structured JSON from text using LLMs and a deep understanding of Prompt Engineering.
• Proficiency in classic NLP libraries for tasks like NER, text classification, and pre-processing.
• Experience with LLM tracing, debugging and evaluation platforms such as Langfuse.
• Excellent communication, organizational, problem-solving, debugging, and analytical skills.

        Great to have 

• Experience in async processing of data at scale
• Using frameworks like LangChain, HuggingFace, and backend web frameworks like FastAPI.
• Expertise on core engineering skills - Cloud, microservice architecture, caching, and queuing.
• Familiarity with concepts/tools as Docker, k8s, VCS, CI/CD
• Previous experience in data extraction from specific domains (e.g., financial reports, news).
  
  

Responsibilities:

• Deploy LLM based production grade solutions.
• Fine-tune and adapt State of the art LLMs for specialized data extraction tasks. Develop innovative prompt engineering strategy and systems to maximize reliability and performance on confidential business documents.
• Solve Engineering challenges that come along with LLM solutions, such as high latency, non-deterministic output, etc.
• Implement and scale data processing pipelines that can process high volumes of complex documents with high accuracy and efficiency.
• Integrate and manage LLM Observability to trace, debug, and monitor every extraction
• Own systems end-to-end, including(but not limited to) designing, coding, monitoring, testing, CI/CD and on-call support.

About Tracelink:

Digital information sharing is the future of medicine. TraceLink is building the first-ever cloud-based network and application platform that helps our global customers share crucial business information while collaborating on manufacturing and distributing billions of medical products

worldwide.

Who you are:

TraceLink is looking for talented full-time software engineers to build products at one of the fastest growing companies in the Pune area. If you’re self-motivated, intellectually curious, and motivated by designing and developing innovative products for global organizations, you could be a good fit for our team.

This is an excellent opportunity to learn and/or extend your knowledge in building large-scale multi-agent systems, define effective strategies for evaluating such systems, and gain hands-on experience in creating and testing non-deterministic software components.

Responsibilities :

The Software Development Engineer in Test assists in building and executing automated tests for

the Company's software products. The SDET will build testing tools to enable automated testing of

the TraceLink platform and application.

• Execute tests on the TraceLink platform and application.

• Extend and maintain automation frameworks.

• Prepare and present clear reports on defect findings that allow developers to quickly and accurately reproduce problems and allow the Quality Engineering team to verify that fixes are complete.

• Verify defect fixes.

• Build tooling for automated testing of the TraceLink platform and application.

• Programmatically interface testing tools with the TraceLink platform and application.

• Create testing tools that can be configured and used by non-developers and can simulate real-world transaction volumes involving potentially millions of transactions per day.

• Provide high-level analysis to apply appropriate technologies and architecture to solve conceptual problems

• Research and remain informed of new technology and tools, and how such technologies could be applied at TraceLink.

•  Work closely with engineers building the core TraceLink product to ensure that testability concerns are factored into the design of the product.

Qualifications :

Candidates must possess the following skills and traits:

• Bachelor's degree or foreign equivalent in computer science, software engineering, or related discipline.

• 2-5 years of progressive, post-baccalaureate experience in a test automation engineering role involving programmatic interaction with a system under test.

• 2-5 years of experience utilizing Java, JavaScript/TypeScript, Eclipse, Ant or Maven, Unix, and an automated unit test framework, such as TestNG.

• 2-5 years of experience developing against web services and Web-based APIs.

• 2-5 years of experience developing and executing formal test plans, data sets, and test configurations for assigned feature areas

• 2-5 years of experience testing web-based enterprise-class business applications.Helpful skills and experience:

Helpful skills and experience:

•  Familiarity with the concepts involved in running cloud-based applications on platforms such as Amazon Web Services.

•  Experience with the pharmaceutical industry.

•  Basic understanding of Large Language Models (LLMs) and generative AI systems.

•  Exposure to testing LLM-based applications, including prompt validation and response evaluation.

•  Familiarity with multi-agent LLM workflows and coordination patterns (e.g., agent orchestration, tool usage, chaining).

•  Experience designing test scenarios for AI systems, including edge cases, hallucination detection, and output consistency checks.

•  Knowledge of evaluation metrics for LLM outputs (e.g., accuracy, relevance, latency, and robustness).

•  Exposure to automation frameworks or tools for validating AI/ML model behavior.

About Tracelink:

Digital information sharing is the future of medicine. TraceLink is building the first-ever cloud-based network and application platform that helps our global customers share crucial business information while collaborating on manufacturing and distributing billions of medical products worldwide.

Tracelink is looking for talented full-time software engineers to build products at one of the fastest-growing companies in the Pune area. If you’re self-motivated, intellectually curious, and motivated by designing and developing innovative products for global organizations, you could be a good fit for our team

Who you are:

Tracelink is looking for talented full-time software engineers to build products at one of the fastest-growing

companies in the Pune area. If you’re self-motivated, intellectually curious and motivated by designing and

developing innovative products for global organizations, you could be a good fit for our team.

This is an excellent opportunity to learn and/or extend your knowledge in building large-scale multi-agent systems, define effective strategies for evaluating such systems, and gain hands-on experience in creating and testing non-deterministic software components.

Responsibilities:

The Software Development Engineer in Test assists in building and executing automated tests for the Company's

software products. The SDET will build testing tools to enable automated testing of the TraceLink platform

and application.

• Build and execute tests on the Tracelink platform and application.

• Build and deploy services for automated testing of the Tracelink platform persistent store.

• Execute performance tests on a Distributed Persistent Data store

• Create testing tools that can simulate real-world transaction volumes.

• Provide high-level analysis to apply appropriate technologies and architecture to solve conceptual problems

• Stay curious, build Innovative solution to new age technical issues

• Influence designs and decision with supporting data

• Work closely with engineers building the core Tracelink product to ensure that testability concerns are factored into the design of the product.

• Extend and maintain automation frameworks to enhance Test coverage

• Prepare and present clear reports on defect findings that allow developers to reproduce problems and allow the Quality Engineering team to verify that fixes are complete quickly and accurately.

• Programmatically interface testing tools with the TraceLink platform and application.

• Work closely with engineers building the core TraceLink product to ensure that testability concerns are factored into the design of the product.

• Research and remain informed of new technology and tools, and how such technologies could be applied at Tracelink.

Qualifications:

Candidates must possess the following skills and traits:

• Bachelor's degree or foreign equivalent in computer science, software engineering, mechanical engineering, or related discipline.

• 5-8 years of progressive, post-baccalaureate experience in a test automation engineering role involving programmatic interaction with a system under test.

• Experience utilizing Java, JavaScript/TypeScript, Eclipse, Ant or Maven, Unix, and an automated unit test framework, such as TestNG.

• Experience developing against web services and Web-based APIs.

• Experience developing and executing formal test plans, data sets, and test configurations for assigned feature areas.

Helpful skills and experience:

• Familiarity with the concepts involved in running cloud-based applications on platforms such as Amazon Web Services.

•  Experience with the pharmaceutical industry.

•  Basic understanding of Large Language Models (LLMs) and generative AI systems.

•  Exposure to testing LLM-based applications, including prompt validation and response evaluation.

•  Familiarity with multi-agent LLM workflows and coordination patterns (e.g., agent orchestration, tool usage, chaining).

•  Experience designing test scenarios for AI systems, including edge cases, hallucination detection, and output consistency checks.

•  Knowledge of evaluation metrics for LLM outputs (e.g., accuracy, relevance, latency, and robustness).

•  Exposure to automation frameworks or tools for validating AI/ML model behavior.

Job Title: Power Platform Engineer (Automation & Copilot Development)

Experience: 3–6 Years

Role Overview

We are looking for a skilled Power Platform Engineer to design, develop, and implement automation solutions across the organization. The ideal candidate will have strong experience in Microsoft Power Platform and hands-on expertise in building AI-powered Copilot agents to streamline business processes, improve efficiency, and drive digital transformation initiatives.

Key Responsibilities

• Design and develop business process automation using:
• Power Automate (Cloud & Desktop)
• Power Apps (Canvas & Model-Driven Apps)
• Power BI (Reports & Dashboards)
• Power Virtual Agents / Copilot Studio
• Build and deploy AI-powered Copilot agents using:
• Microsoft Copilot Studio
• Azure OpenAI integrations (if applicable)
• Custom connectors & APIs
• Automate repetitive organizational tasks and workflows across departments (HR, Finance, Operations, IT, etc.)
• Integrate Power Platform solutions with:
• Microsoft 365 (SharePoint, Teams, Outlook, OneDrive)
• Dynamics 365
• Third-party systems via APIs
• Develop governance, security, and environment strategies for Power Platform
• Create reusable components, flows, and automation frameworks
• Monitor performance and optimize automation solutions
• Provide technical documentation and user training
• Collaborate with business stakeholders to gather requirements and translate them into scalable technical solutions

Required Skills & Qualifications

• Bachelor’s degree in Computer Science, IT, or related field
• 3+ years of hands-on experience with Microsoft Power Platform
• Strong experience in:
• Power Automate
• Power Apps
• Dataverse
• REST APIs & connectors
• Experience building Copilot agents using Microsoft Copilot Studio
• Understanding of AI/LLM-based automation concepts
• Knowledge of SharePoint Online & Microsoft Teams integration
• Strong problem-solving and analytical skills
• Experience in environment management and DLP policies

Preferred Skills

• Experience with:
• Azure services (Azure Functions, Logic Apps)
• PowerShell scripting
• Microsoft Graph API
• CI/CD for Power Platform
• PL-900 / PL-100 / PL-200 / PL-400 certifications
• Experience working in enterprise automation projects

About Convera

• Convera is the largest non-bank B2B cross-border payments company in the world. Formerly Western Union Business Solutions, we leverage decades of industry expertise and technology-led payment solutions to deliver smarter money movements to our customers – helping them capture more value with every transaction.
• Convera serves more than 30,000 customers ranging from small business owners to enterprise treasurers to educational institutions to financial institutions to law firms to NGOs.
• Our teams care deeply about the value we bring to our customers which makes Convera a rewarding place to work. This is an exciting time for our organization as we build our team with growth-minded, results-oriented people who are looking to move fast in an innovative environment.
• As a truly global company with employees in over 20 countries, we are passionate about diversity; we seek and celebrate people from different backgrounds, lifestyles, and unique points of view. We want to work with the best people and ensure we foster a culture of inclusion and belonging.
• We offer an abundance of competitive perks and benefits including:
• Competitive salary
• Opportunity to earn an annual bonus
• Great career growth and development opportunities in a global organization
• A flexible approach to work

#LI-KP1

About the Role:
As a Senior AI Engineer, you will help architect, build and implement our AI platforms, working closely with data quality engineers, data/software engineers, platform engineers, DevOps, product owners and business.  You provide technical leadership for multiple, diverse, and geographically distributed teams. You will coach and guide teams to enable future success. Also be a partner with engineering managers, directors and VP on strategic initiatives and future business growth opportunities especially around AI and ensuring the engineering organization can scale to meet the need.

As a member of the engineering team, you are responsible for coaching, mentoring, and driving change to enable us to better deliver and innovate in an agile environment.

Your day to day:

• Help shape the direction of our applied AI areas and intelligence features in our products. Drive the deployment of state-of-the-art AI models and systems that directly impacts on the capabilities and performance of Abacus’s products and services (e.g., Abacus Agents, MCP, SQL and RAG agents and tools, etc.)
• Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains
• Design and implement ML/AI pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation, iteration and self-healing
• Work closely with cross-functional teams, including AI engineers, data engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction
• Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model and GenAI system performance
• Skillful at driving critical projects (e.g. AI and data engineering Innovation, Development Productivity and Benchmarking)
• Meaningful experience in the world of Data and AI
• Capable of credible customer interactions
• Mentoring development team members to ensure delivered solutions adhere to the software architecture strategy, coding standards, and established organizational policies and procedures
• Participating in software architectural discussions, influencing decisions, and collaborating with peers to maintain consistency across the organization
• Identifying people and process improvement strategies for the Agile/Scrum team(s), especially for AI projects/teams where innovation and iteration are critical
• Communicate organizational updates to ensure teams adhere to the established policies and procedures
• Ensure projects are completed on time and according to our quality standards
• Facilitates communication upward around architecture, design, and implementation objectives
• Proven experience in leading software development teams or projects
• Excellent knowledge of software development design, QA and test automation, and experience with agile development methodologies
• Demonstrated knowledge of Cloud Architecture, AI Architecture, Agents/Agentic systems, Massive Parallel Processing (MPP) compute frameworks for Data+AI platforms, Security, and MCP/API based services
• Good understanding of Incident Management, Configuration Management, Operational efficiency and Customer Escalation Management preferred. Can manage the balance of deliveries on our roadmap commitments while dealing with interruptions and client escalations
• Good experience with open source
• Coach and mentor software and AI developers, develop staff skills, provide continuous feedback 
• Has relentlessly high standards (is never satisfied with the status quo)
• Responsible for protecting, securing, and proper handling of all confidential data held by Abacus to ensure against unauthorized access, improper transmission, and/or unapproved disclosure of information that could result in harm to Abacus or our clients.

What you bring to the team:

• Minimum of 3 years of ML/AI engineering experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML/AI research in academia will be considered as contributing qualification
• Minimum of 3 years of experience as a software developer at some point in career
• Minimum of 2 years of experience with Databricks, Mosaic AI Gateway and associated technologies in Databricks stack related to Data and AI engineering
• Strong track record of working with language modeling technologies and GenAI. This could include the following: Developing generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, evaluation benchmarks, Agents and Agentic workflows (e.g. orchestration, workflow management, observability, debugging), RAG, SQL Agents, MCP, etc.
• Proficiency in Python, TensorFlow/PyTorch, and scalable ML/AI architecture
• Ability to drive end-to-end model and system development, from research and prototyping to deployment and monitoring
• Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment
• Experience and good understanding of designing scalable, distributed systems for running small to medium scale data processing applications and services (10s – 100s of TBs of data)
• Possesses a level of breadth and depth of software and AI development experience that allows for influence and competence in technical discussions with internal and external stakeholders
• Solid understanding of roles adjacent to the software development (product management, project management, client delivery, operations etc.). Ability to adapt to these roles as defined at Abacus and work with others in these roles
• Proven record of success of driving and/or leading engineering teams/projects towards developing production grade systems supporting customers
• Nice to have experience with, but not required: Snowflake, FHIR, Healthcare Data exposure

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST