Lead - AI Engineer / DVP - AI Engineering

Emkay Global; India; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Emkay Global is seeking a Lead AI Engineer to architect, build, and scale production-grade AI and ML solutions. This hands-on leadership role requires deep technical expertise and the ability to guide teams in delivering secure, reliable AI platforms across digital products and enterprise systems.

You will lead Generative AI workloads, RAG pipelines, multi-agent workflows, and platform APIs, while establishing governance, performance optimization, and cost efficiency.

Qualifications

• 8+ years of professional software/AI experience.
• 2–3+ years building Generative AI/LLM in production.
• Bachelor’s or Master’s in CS/AI/Engineering; advanced certs a plus.
• Experience delivering AI in regulated or enterprise-scale environments is preferred.

Responsibilities

• Lead design, development, and deployment of scalable AI platforms end-to-end.
• Architect Retrieval-Augmented Generation pipelines and vector stores.
• Guide multi-agent workflows and tool-use automations in business processes.
• Build secure, scalable APIs (REST/gRPC) exposing AI capabilities.
• Establish governance, evaluation, safety, and compliance for AI solutions.
• Mentor engineers and set coding standards for reusable AI components.

Skills

Technical leadership

Mentorship

Communication

Problem solving

Cross-functional collaboration

Education

Bachelor’s or Master’s in CS/AI/Engineering

Tools

Python

LangChain

LlamaIndex

AutoGen

PyTorch

TensorFlow

OpenAI

Anthropic

Llama

Mistral

vLLM

Ollama

Job description

8 - 10 Years

Full Time

Job Description

We are seeking a highly experienced and hands-on Lead AIEngineer to architect, build, and scale production-grade ArtificialIntelligence and Machine Learning solutions. This role requires deep technicalexpertise, strong engineering discipline, and the ability to guide teams intranslating AI concepts into secure, reliable, and business-ready platforms.

You will lead advanced AI workloads including Generative AIapplication development, Retrieval-Augmented Generation, agentic workflows,predictive modeling, and intelligent automation. You will also providetechnical direction, mentor engineers, establish engineering best practices,and ensure AI solutions deliver measurable impact across digital platforms.

• Technical Leadership:Lead the design, development, and deployment of scalable AI and Generative AIsolutions, providing technical direction across architecture, implementation,and production readiness.
• AI SolutionArchitecture: Architect robust Retrieval-Augmented Generation pipelines,vector search systems, model orchestration layers, and enterprise-grade AIservices.
• Agentic & AutonomousWorkflows: Design and guide the development of multi-agent AI systemscapable of executing complex business processes, tool use, reasoning, andworkflow automation.
• Platform & APIEngineering: Build and oversee secure, scalable REST or gRPC services thatexpose AI capabilities to digital products, backend platforms, and enterprisesystems.
• Evaluation, Governance& Guardrails: Establish AI evaluation frameworks, quality benchmarks,content safety controls, hallucination mitigation strategies, and responsibleAI practices.
• Performance & CostOptimization: Optimize models, prompts, embeddings, inference workloads,and infrastructure to improve latency, reliability, token efficiency, and cloudcost effectiveness.
• Mentorship &Engineering Excellence: Mentor engineers, conduct technical reviews, definecoding standards, and promote reusable AI components, testing practices,documentation, and operational discipline.
• Programming Languages:Expert proficiency in Python with strong software engineeringfundamentals, clean architecture, testing practices, and performance-awaredevelopment.
• AI Frameworks:Advanced hands-on experience with LangChain, LlamaIndex, AutoGen, orsimilar orchestration frameworks, along with deep learning frameworks such as PyTorchor TensorFlow.
• LLMs & FoundationModels: Proven experience selecting, fine-tuning, prompting, evaluating,and deploying commercial and open-weight models including OpenAI, Anthropic,Llama, Mistral, vLLM, Ollama, or equivalent platforms.
• Vector Databases:Strong experience designing semantic search and retrieval systems using Pinecone,Milvus, Qdrant, pgvector, or similar vector database technologies.
• MLOps & CloudInfrastructure: Strong experience with model lifecycle management,deployment automation, observability, CI/CD, containerization, and cloud AIplatforms such as AWS SageMaker, AWS Bedrock, or equivalent services.
• Data Engineering &Pipelines: Solid understanding of SQL, distributed data processing,orchestration tools such as Apache Airflow or Prefect, and reliable dataingestion for AI training, retrieval, and contextual grounding.

• Experience: 8+ years of professional experience insoftware engineering, machine learning, or applied AI, with at least 2–3+ yearsbuilding and shipping Generative AI, LLM, or ML products into production.
• Industry Background:Experience delivering AI systems in regulated or large-scale digitalenvironments such as Fintech, Banking, E-commerce, Healthcare, or enterpriseplatforms is highly preferred.
• Education:Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence,Data Science, Engineering, or an equivalent technical discipline; advancedcertifications or open-source contributions are a plus.

Core Competencies

• Technical Ownership:Ability to own complex AI platforms end to end, from problem framing andarchitecture through delivery, monitoring, optimization, and continuousimprovement.
• Responsible AILeadership: Strong awareness of data privacy, bias mitigation, security,explainability, model governance, and safe deployment practices.
• Mentorship &Collaboration: Ability to mentor engineers, influence cross-functionalstakeholders, communicate complex AI concepts clearly, and drive practicaladoption of emerging AI technologies.