We are seeking a Senior / Lead AI Software Engineer to join an advanced R&D innovation initiative building a next-generation meta-prompting, context engineering, and centralized knowledge management system for AI coding agents. In this hands-on engineering role, you will build and implement production-grade, LLM-powered applications that provide structured context (rules, skills, workflows, sub-agents) to guide AI systems in operating with a deep understanding of system architecture, domain constraints, and engineering standards. As a technical lead on the squad, you will write robust code for developer-facing AI infrastructure, build advanced RAG pipelines, and accelerate project onboarding by reverse-engineering architecture and domain context, while mentoring mid-level developers in a fast-paced R&D environment.
Essential functions
- Design, build, and deploy production-grade LLM-powered services, microservices, and APIs using Python and TypeScript.
- Implement advanced meta-prompting frameworks (controlling and guiding models through formalized languages) and prompt optimization techniques to ensure deterministic, context-aware AI outputs.
- Develop scalable Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases (such as Pinecone, Weaviate, or ChromaDB) for deep context engineering and semantic code search.
- Orchestrate LLM workflows using frameworks like LangChain or LlamaIndex to connect multi-agent tools, system constraints, and domain knowledge bases.
- Implement automated testing, LLM evaluation, and quality assurance frameworks to benchmark model performance, accuracy, and output consistency.
- Build containerized microservices and automated CI/CD pipelines using Docker to support seamless deployment and sandboxed execution.
- Act as a hands-on Senior Developer and Mentor, guiding mid-level engineers, establishing coding standards, and conducting thorough code reviews.
Qualifications
- 5+ years of commercial software development experience, with a proven track record of writing production-grade code in both Python and TypeScript.
- Strong hands-on experience integrating major LLM APIs (OpenAI, Anthropic Claude) into production software.
- Deep expertise in meta-prompting (model control via formalized languages), advanced prompt engineering, and context window optimization.
- Practical experience building and deploying Retrieval-Augmented Generation (RAG) systems using vector databases (e.g., Pinecone, Weaviate, ChromaDB).
- Solid hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex, or similar) and embedding models.
- Demonstrated experience developing automated testing, evaluation, and observability pipelines for AI/LLM applications.
- Strong proficiency in containerization with Docker, API design, and CI/CD automation pipelines.
- Experience as a Senior/Lead Developer or Technical Mentor in a fast-paced R&D environment.
- Excellent problem-solving skills, software engineering discipline, and written/verbal English communication capabilities.
Would be a plus
- Experience with multi-agent architecture, agent orchestration, and progressive disclosure patterns in AI applications.
- Practical knowledge of Model Context Protocol (MCP) or emerging context-sharing standards for AI agents.
- Hands-on experience with LLM-as-a-Judge evaluation methodologies and A/B testing frameworks for GenAI systems.
- Experience building developer tools, CLI utilities, or software development kits (SDKs).
- Familiarity with OAuth/OIDC security and enterprise authentication protocols.
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI,
and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical
challenges and enable positive business outcomes for enterprise companies undergoing business transformation.
A key differentiator for Grid Dynamics is our 8 years of experience and leadership in
enterprise AI, supported by profound expertise and ongoing investment in
data,
analytics,
cloud & DevOps,
application modernization
and
customer experience.
Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.