Responsibilities
- Build RAG pipelines, AI assistants, agent workflows, AI gateway components, MCP-based integrations and reusable platform elements
- Implement Azure AI solutions using Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Azure API Management, AKS, Azure Container Apps, Key Vault, Cosmos DB and monitoring tools
- Deliver AI-native engineering workflows using GitHub Copilot, GitHub Actions, GitHub Advanced Security and secure pull-request patterns
- Apply harness engineering patterns for AI systems, including agent instructions, tool contracts, retrieval grounding, evaluation suites, telemetry, safety checks, cost tracking and human approval gates
- Build CI/CD pipelines, IaC automation, observability stacks and deployment frameworks for AI workloads
- Create reusable templates, reference implementations, demos and onboarding kits for client teams
- Own one or more implementation workstreams such as retrieval, orchestration, AI gateways or Copilot enablement
- Mentor engineers, review code and support architecture decisions for AI-assisted engineering adoption
Basic qualifications
- 6+ years of experience in software engineering, cloud engineering, DevOps or platform engineering
- Hands-on experience with GenAI, RAG, agentic systems, copilots and AI platform automation
- Proven coding skills in Python, TypeScript, C#, Java or Go for production-grade APIs, back-end services and infrastructure automation
- Strong experience with Microsoft Azure and cloud-native architectures
- Knowledge of containers, Kubernetes, serverless models and Infrastructure-as-Code practices
- Familiarity with security, identity, logging, monitoring, cost optimization and operational readiness principles
- Ability to demonstrate production-ready AI systems: tested, deployed, monitored and supported at scale
- Practical experience mentoring teams and guiding AI-assisted SDLC with quality and governance in mind
- Strong communication and collaboration skills adaptable to both technical and business environments
Preferred qualifications
- Deep knowledge of Microsoft Foundry, Azure OpenAI, Azure AI Search and related Azure AI services
- Experience with GitHub toolchains including Copilot, GitHub Actions, Advanced Security and MCP-based integrations
- Practical knowledge of RAG implementations: hybrid search, embeddings, semantic ranking and evidence capture
- Familiarity with agent frameworks such as Semantic Kernel, Microsoft Agent Framework, LangChain, AutoGen and similar
- Strong programming skills in multiple languages (Python, TypeScript, C#, Java, Go)
- Experience in evaluation and agent reliability engineering: golden datasets, regression tests, prompt-injection defense, state handling, retries, recovery and feedback loops
- Exposure to Microsoft 365 Copilot integrations (Graph, Teams, SharePoint, Power Platform)
- Familiarity with other AI ecosystems like AWS Bedrock, Google Vertex AI, Databricks, Anthropic, Hugging Face or Snowflake
- 26 paid holiday days
- Pension plan scheme
- Disability insurance (WGA Shortfall insurance)
- Long-term disability insurance (WIA Top up insurance)
- EPAM Employee Stock Purchase Plan (ESPP)
- Commuting to work - costs reimbursement
- Laptop + corporate simcard + corporate mobile device (subject to certain eligibility requirements)
- Bike lease
- Employee Assistance Program
- Corporate Programs including Employee Referral Program with rewards
- Learning and development opportunities including in-house training and coaching, professional certifications, and courses
Tags & focus areas
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