Skip To Main Content
epam-logo-black.svgepam-logo-black.svg
backBack to Search

Applied Senior Software Engineer (AI Native Development)

Hybrid in Singapore
AI Engineering& 7 others
hot
Looking for something else?

Find a vacancy that works for you. Send us your CV to receive a personalized offer.

Find me a job

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 generating, refactoring and documenting complex codebases at scale
  • Champion the shift from manual coding to an agentic workforce while maintaining 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 agentic workflows featuring tool use, memory and multi-step reasoning focused on engineering tasks
  • Strong understanding of RAG architectures, prompt engineering and the mechanics of AI integration into production-grade SDLC workflows
  • Execution-focused mindset with a strong preference for build, test and ship 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