Lead design, development, and deployment of production-grade Generative AI applications (LLM-based chatbots, agents, RAG systems). Hands-on coding in Python, integrate and benchmark models, build ingestion and vector retrieval pipelines, design architecture for performance and cost, mentor engineers, and implement AI governance, safety, and monitoring.
Job Title: Generative AI Technical Lead Overview
We are seeking a Hands-on Generative AI Technical Lead to design, build, and scale AI-powered applications using state-of-the-art large language models (LLMs) and multimodal systems. This role combines deep technical expertise with leadership, requiring active coding, architecture ownership, and mentorship of engineering teams.
Key Responsibilities- Lead end-to-end GenAI development
- Design, develop, and deploy LLM-based applications (chatbots, copilots, agents, RAG systems)
- Build scalable, production-grade AI systems
- Hands-on engineering
- Write high-quality code (Python, APIs, pipelines)
- Implement prompt engineering, fine-tuning, embeddings, and vector search
- Work directly with frameworks like LangChain, LlamaIndex, or similar
- Architecture & system design
- Define GenAI architecture (RAG, agents, tool use, orchestration)
- Optimize performance, latency, and cost of AI systems
- Model integration
- Integrate with OpenAI, Anthropic, open-source models (Llama, Mistral, etc.)
- Evaluate and benchmark models for use cases
- Data & retrieval systems
- Design vector databases (Pinecone, Weaviate, FAISS, etc.)
- Build ingestion pipelines and knowledge retrieval systems
- Team leadership
- Mentor engineers and guide best practices
- Conduct code reviews and technical design reviews
- Experimentation & innovation
- Stay current with GenAI trends (agents, multimodal, fine-tuning, evals)
- Rapidly prototype and validate new ideas
- AI governance & safety
- Implement guardrails, monitoring, and evaluation frameworks
- Ensure responsible and secure AI usage
- 10+ years of software engineering experience
- Strong programming skills in Python
- Experience with:
- LLM APIs (OpenAI, Anthropic, etc.)
- RAG pipelines and vector databases
- Prompt engineering and evaluation techniques
- Solid understanding of:
- NLP concepts, embeddings, transformers
- Distributed systems and cloud platforms (AWS/GCP/Azure)
- Experience building and deploying APIs and microservices
-
Compensation, Benefits and Duration
Minimum Compensation: USD 62,000
Maximum Compensation: USD 217,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
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