NP : Immediate joiners or 15days notice period
Number of Openings: 1
Job Description
We are seeking an experienced AI Technical Lead to drive the design, development, and implementation of enterprise-grade AI solutions. The ideal candidate will possess strong hands-on experience building and deploying AI applications in production environments and will provide both technical leadership and execution support to development teams.
This role requires a balance of solution architecture, hands-on development, mentoring, and delivery ownership to ensure AI initiatives are scalable, secure, reliable, and aligned with business objectives.
7–12 Years (with minimum 3+ years in AI/ML and Generative AI solution development)
Key Responsibilities
Technical Leadership
- Define and review AI solution architectures and implementation approaches.
- Guide engineering teams on best practices for AI application development.
- Identify technical risks, implementation gaps, and optimization opportunities.
- Ensure AI solutions meet performance, scalability, security, and maintainability requirements.
Hands-on Development
- Design and develop AI-powered applications and workflows.
- Build and optimize Retrieval-Augmented Generation (RAG) solutions.
- Develop AI agents, orchestration workflows, and automation solutions.
- Integrate LLMs with enterprise applications, APIs, databases, and third-party systems.
- Support deployment, testing, monitoring, and troubleshooting of AI solutions in production environments.
Mentoring & Team Enablement
- Provide technical mentorship to developers and junior AI engineers.
- Conduct code reviews and architecture reviews.
- Establish development standards, reusable frameworks, and implementation guidelines.
- Help teams translate business requirements into effective AI solutions.
Governance & Quality
- Define evaluation frameworks and success metrics for AI solutions.
- Implement observability, monitoring, and performance tracking.
- Ensure compliance with security, privacy, and responsible AI practices.
- Drive continuous improvement through experimentation and adoption of emerging AI technologies.
Required Skills
Generative AI & LLMs
- Strong experience working with OpenAI, Anthropic Claude, Gemini, or similar LLMs.
- Expertise in prompt engineering and prompt optimization.
- Experience building RAG-based applications.
- Knowledge of AI agent frameworks and orchestration patterns.
- Understanding of model evaluation, grounding, hallucination mitigation, and AI quality assurance.
AI Engineering
- Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar frameworks.
- Experience integrating vector databases such as Pinecone, Weaviate, Chroma, or Qdrant.
- Knowledge of embeddings, semantic search, and retrieval techniques.
- Experience implementing AI workflows and automation solutions.
Software Engineering
- Strong programming skills in Python.
- Experience with REST APIs and microservice architectures.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Understanding of CI/CD, deployment pipelines, and DevOps practices.
- Experience working with SQL and NoSQL databases.
Production Experience
- Proven experience delivering AI solutions to production environments.
- Experience monitoring and optimizing AI application performance.
- Strong troubleshooting and debugging capabilities for AI systems at scale.
Preferred Qualifications
- Experience leading AI teams or mentoring engineers.
- Experience building enterprise AI assistants, copilots, chatbots, or workflow automation solutions.
- Familiarity with MLOps and AI governance practices.
- Exposure to manufacturing, ERP, inventory, or field service domains is a plus.
Key Success Criteria
- Successful delivery of production-ready AI solutions.
- Improved development velocity through technical leadership and mentoring.
- Reduced implementation rework and technical debt.
- Establishment of scalable AI engineering practices and standards.
- High-quality, maintainable, and secure AI implementations.
