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Tech Stack
Tools & technologiesAWSAzureCloudDockerGoGoogle Cloud PlatformGRPCKubernetesMicroservicesNoSQLNumpyPandasPythonReactSQL
About the role
Key responsibilities & impact- Design, develop, and deploy applications and microservices in Golang and Python that leverage AI/ML capabilities
- Architect and build AI agents — multi-step reasoning workflows, tool/function calling, memory, planning, and orchestration — using frameworks like LangChain, LangGraph, CrewAI, or custom agentic loops
- Build and integrate solutions using LLM APIs (Anthropic, OpenAI, etc.) including RAG pipelines, prompt engineering, and vector database integrations (pgvector, Pinecone, FAISS)
- Use AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) effectively for rapid prototyping, refactoring, test generation, and agent-driven coding workflows
- Develop high-performance backend services and APIs (Gin/Echo/gRPC in Go; FastAPI in Python)
- Write clean, testable, production-grade code with proper version control (Git) and CI/CD practices
- Collaborate with cross-functional teams to translate business problems into AI-driven solutions
Requirements
What you’ll need- A related bachelor's degree in Computer Science, Information Technology, or a related field or any STEM degree (Science, Technology, Engineering or Mathematics)
- Approximately 3-6 of experience in related field will be an advantage.
- Strong hands-on Golang development: goroutines, channels, concurrency patterns, building high-performance microservices, gRPC, and CLIs
- Strong hands-on Python development (3+ years): OOP, async programming, common libraries (Pandas, NumPy)
- Deep practical understanding of building AI agents — agent architectures (ReAct, plan-and-execute), tool calling, MCP (Model Context Protocol), context/memory management, and agent evaluation.
- Demonstrated experience using AI coding tools (Claude Code, GitHub Copilot, etc.) as part of the development workflow — agentic coding, spec-driven development, and prompt-based engineering, not just autocomplete.
- Solid AI/ML fundamentals: how LLMs work, embeddings, fine-tuning vs. RAG, evaluation basics.
- Working knowledge of SQL/NoSQL databases; exposure to vector databases is a plus.
- Familiarity with cloud platforms (AWS/Azure/GCP), Docker, and Kubernetes basics.
Benefits
Comp & perks- Support, coaching, and feedback from some of the most engaging colleagues around.
- Opportunities to develop new skills and progress your career.
- The freedom and flexibility to handle your role in a way that’s right for you.
- Competitive remuneration package where you’ll be rewarded for your individual and team performance.
- Comprehensive Total Rewards package includes support for flexible working and career development.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
GolangPythonAI/MLmicroservicesgRPCFastAPIOOPasync programmingSQLNoSQL
Soft Skills
collaborationproblem-solvingcommunication
Certifications
bachelor's degree in Computer Sciencebachelor's degree in Information TechnologySTEM degree
