
Engineering Lead for Genomic Data Intelligence
7 hours ago
We are seeking a highly experienced GenAI Engineer with expertise in Prompt Engineering, Retrieval-Augmented Generation (RAG), and Vector Search Systems to integrate GenAI into our engineering & DevOps ecosystem.
This is a contractor role where you will design intelligent assistants & agents to augment CI/CD workflows, knowledge retrieval, incident handling, and developer productivity using LLMs, Python, and NLP pipelines.
Key Responsibilities:
- Design & optimize prompts for LLM workflows ensuring accuracy & relevance
- Build RAG pipelines using vector DBs (FAISS, Pinecone, Weaviate, Qdrant)
- Integrate LLMs into internal tools, CI/CD & observability dashboards
- Implement GenAI solutions using LangChain, LlamaIndex, Haystack, Hugging Face etc.
- Fine-tune open-source/commercial LLMs (OpenAI, Claude, Cohere, Mistral) for domain use cases
- Collaborate with DevOps & platform teams to drive automation with GenAI
- Ensure data privacy, governance & ethical AI practices
Required Skills:
- 6–10+ years in engineering, with 2+ years hands-on in GenAI/LLMs/NLP
- Strong Python skills with experience in LangChain, Hugging Face, LlamaIndex
- Deep knowledge of vector databases & embeddings
- Proven experience designing & deploying RAG architectures
- Experience integrating LLM APIs (OpenAI, Azure OpenAI, Claude, etc.)
Nice to Have:
- Experience with multi-modal models / fine-tuning LLMs
- Familiarity with developer-facing GenAI use cases: infra-as-code review, changelog generation, log triage
- Exposure to Kubernetes, GitOps, DevSecOps
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