Technical Lead GenAI / LLM Solutions

Tekskills

Bengaluru

On-site

INR 350,000 - 750,000

Full time

10 days ago

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Job summary

Tekskills in Bengaluru seeks a hands-on Technical Lead with deep GenAI expertise to lead delivery of a client-facing GenAI platform. The role combines LLM system design, engineering excellence, and client communication to translate business problems into production-ready AI capabilities.

You will own end-to-end delivery, act as the technical lead for clients, and mentor engineers while ensuring performance, cost efficiency, security, and responsible AI compliance.

Qualifications

  • 10-15 years of software engineering experience, 4+ years in a Tech Lead role
  • Hands-on delivery of GenAI/LLM solutions in production
  • Experience working with clients or external stakeholders
  • Strong experience with LLM platforms (Azure OpenAI, OpenAI,Anthropic, or open-source)
  • Deep understanding of RAG, embeddings, and vector databases
  • Experience with GenAI frameworks (LangChain, LlamaIndex, Semantic Kernel)
  • Strong programming in Python (preferred) and/or JavaScript/TypeScript
  • Experience with cloud platforms (AWS, Azure, GCP), APIs, and microservices
  • CI/CD and DevOps/MLOps exposure

Responsibilities

  • Own end-to-end technical delivery of GenAI solutions for the Genie Project
  • Act as the primary technical point of contact for clients
  • Hands-on design, development, review, and optimization of GenAI and backend code
  • Architect and implement LLM-based systems (RAG, agents, prompt workflows)
  • Translate client requirements into scalable, secure technical solutions
  • Guide best practices for prompt engineering, model usage, evaluation, and observability
  • Mentor engineers and ensure high engineering and delivery standards
  • Ensure performance, cost efficiency, security, and responsible AI compliance
  • Support client demos, technical discussions, and solution walkthroughs

Skills

LLM systems
Python
TypeScript/JavaScript
Cloud platforms
MLOps
RAG architectures
Embeddings
Prompt engineering
Leadership
Client interaction

Tools

LangChain
LlamaIndex
Semantic Kernel

Job description

Job Summary

We are looking for a hands-on Technical Lead with deep GenAI expertise to lead delivery of a client-facing GenAI platform. This role requires strong technical leadership, active coding, and the ability to work closely with clients to define, design, and deliver scalable GenAI solutions. The ideal candidate combines LLM system design, engineering excellence, and client communication skills to translate business problems into production-ready AI capabilities.

Responsibilities
  • Own end-to-end technical delivery of GenAI solutions for the Genie Project
  • Act as the primary technical point of contact for clients
  • Be actively hands-on with design, development, review, and optimization of GenAI and backend code
  • Architect and implement LLM-based systems (RAG, agents, prompt workflows)
  • Translate client requirements into scalable, secure technical solutions
  • Guide best practices for prompt engineering, model usage, evaluation, and observability
  • Mentor engineers and ensure high engineering and delivery standards
  • Ensure performance, cost efficiency, security, and responsible AI compliance
  • Support client demos, technical discussions, and solution walkthroughs
Required Skills & Experience
  • 10-15 years of software engineering experience; 4+ years in a Tech Lead role
  • Proven hands-on experience delivering GenAI / LLM solutions in production
  • Experience working directly with clients or external stakeholders
  • Strong experience with LLM platforms (Azure OpenAI, OpenAI, Anthropic, or open-source models)
  • Deep understanding of RAG architectures, embeddings, and vector databases
  • Experience with GenAI frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.)
  • Strong programming skills in Python (preferred) and/or JavaScript/TypeScript
  • Experience with cloud platforms (AWS, Azure, or GCP), APIs, and microservices
  • CI/CD and DevOps/MLOps exposure
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