Applied Senior Software Engineer (AI Native Development)

Office in Hong Kong S.A.R

AI Engineering

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EPAM Systems is a global team of technologists who design, develop and deliver software that powers the world. We are at a pivotal moment where AI is the core engine of our engineering craft.

Join our AI-Centric Delivery team as a Senior Software Engineer to redefine the Software Development Lifecycle (SDLC). Go beyond writing code to design and orchestrate AI agents and agentic workflows that accelerate development velocity.

If you are a tool-agnostic engineer focused on the future of AI-native engineering, this role offers the opportunity to build, test and ship transformative technical solutions for global brands.

Responsibilities

Design and build sophisticated AI developer agents capable of generation, refactoring and documentation of complex codebases at scale
Champion the shift from manual coding to an agentic workforce while maintenance of hands-on technical involvement for high-level precision
Deliver functional, high-velocity prototypes in tight windows to prove the real-world power of AI-driven engineering
Design and integrate AI-enabled workflows directly into the engineering stack, including Git, Jira and CI/CD pipelines, to automate processes and maximize developer throughput
Consult with stakeholders to translate complex business requirements into AI-SDLC-augmented technical solutions
Articulate the trade-offs of agentic design and ensure alignment with enterprise goals

Requirements

Extensive engineering background as a high-performing developer with mastery of Java, JavaScript, Python or .NET
Hands-on expertise with large language models including Anthropic Claude, OpenAI GPT or Google Gemini
Proven capability in development of agentic workflows that feature tool use, memory and multi-step reasoning focused on engineering tasks
Strong understanding of RAG architectures, prompt engineering and the mechanics of integration of AI into production-grade SDLC workflows
Execution-focused mindset with a strong preference for construction, tests and shipment of working solutions

Nice to have

Experience with multi-agent orchestration frameworks like CrewAI or AutoGen
Knowledge of vector databases such as FAISS, Pinecone, Qdrant or Chroma
Familiarity with LLM evaluation, guardrails and observability
Cloud deployment experience with AWS, Azure or GCP
Practical experience with AI frameworks such as LangChain, Hugging Face or LlamaIndex