Lead AI Engineer with .NET

Epam Systems — Kyrgyzstan · Posted ~1 day ago

Lead

Skills

AI/ML .NET Software Architecture Natural Language Processing Summarization Intelligent Validation Exception Handling Workflow Assistance Model Gateway Prompt Registry Retrieval Services Vector Stores Evaluation Auditability Human-in-the-loop Team Leadership GCP Azure C# Python PyTorch TensorFlow Vector Databases Kubernetes AWS CI/CD

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Summary ✨ AI‑Generated

We are seeking a Lead AI Engineer to drive integration of AI-based features into measurement products. You will own the architecture of AI features including natural-language query, summarization, intelligent validation, exception handling, and workflow assistance. Integrate with model gateway, prompt registry, retrieval services, and vector stores. Ensure evaluation, auditability, and human-in-the-loop patterns for regulated workflows. Lead a small engineering team and establish reusable AI feature patterns.

Highlights

Own AI feature architecture for regulated measurement products, integrate with established AI/data platform, lead small engineering team, establish reusable AI patterns.

Description

We are seeking a Lead AI Engineer to drive the integration of AI-based features into measurement products. In this role, you will own the architecture of these features and ship them against an established AI/data platform, rather than building the platform itself. Your work will span natural-language query, summarization, intelligent validation and exception handling and workflow assistance, integrating with a model gateway, prompt registry, retrieval services and vector stores. Since outputs feed regulated measurement workflows, evaluation, auditability and human-in-the-loop patterns are central to the job, and you will be accountable for the work of a small engineering team. Responsibilities Own the architecture of AI features and ship them, including natural-language query, summarization, intelligent validation and exception handling, and workflow assistanceEstablish and evangelize reusable AI feature patterns for retrieval, evaluation and guardrails so teams do not reinvent them per productImplement RAG end to end: chunking, embeddings, hybrid search, reranking, and grounded responses with citationsDrive prompt and context engineering, including multi-step and agentic flows where they add product valueDefine evaluation discipline, including golden datasets, offline eval suites, LLM-as-judge approaches and per-release regression checksDefine and document complex requirements with stakeholders across product features, evaluation criteria and responsible-AI constraintsLead and mentor a small engineering team on LLM integration and evaluation, taking accountability for their workManage cost, latency and reliability through caching, fallbacks, token budgets and graceful degradationIntegrate with platform services such as model gateway, prompt registry, vector stores and embedding pipelinesApply responsible-AI practice, including tenant data isolation, auditability, OWASP LLM Top 10 mitigations and human-in-the-loop patternsInstrument telemetry via Application Insights and Serilog Requirements 8+ years of software engineering experience in .NET (C#) and/or Python, with lead-level ownership of AI feature architecture across one or more productsProven background in shipping LLM-based features to production, including tool and function calling, structured outputs and streamingProficiency with Azure OpenAI / Azure AI Foundry, OpenAI or Anthropic APIsWorking knowledge of the component parts of a modern AI/data platform and how to build against them: model gateway, prompt registry, vector storesFamiliarity with embedding pipelines, evaluation frameworks, LLM observability and guardrailsJudgment about where AI adds product value and where deterministic logic is the better toolSolid SQL fundamentals and API integration skillsStrong documentation and standards habits, including architecture docs in Azure DevOps Wiki, code review and testing disciplineHands-on experience using AI coding agents in the SDLC such as GitHub Copilot, Claude or equivalentCapability to work in agentic automation pipelines, including AI-driven PR review and QA acceptance flows triggered by ADO work item tagsEnglish proficiency at an Upper-Intermediate level (B2) or higher We offer We connect like-minded people:Delivering innovative solutions to industry leaders, making a global impactEnjoyable working environment, whether it is the vibrant office or the comfort of your own homeOpportunity to work abroad for up to two months per yearRelocation opportunities within our offices in 55+ countriesCorporate and social eventsWe invest in your growth:Leadership development, career advising, soft skills and well-being programsCertifications, including GCP, Azure and AWSUnlimited access to EPAM's internal learning databaseFree English classes with certified teachersWe cover it all:Monetary bonuses for engaging in the referral programMedical & family care packageSix trust days per year (sick leave without a medical certificate)Coverage of psychology sessions of your choiceDiscounts for fitness clubs and sports programsBenefits package (sports activities, a variety of stores and services) EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments. Experience the freedom of remote work from anywhere in Kyrgyzstan, whether it's the comfort of your home or our modern office in Bishkek.