Technical Lead-AI ML

Job Description Technical Lead (AI/ML & Generative AI)

Position: Technical Lead – AI/ML & Generative AI

Location: Trivandrum, Kerala

Job Summary

We are seeking a highly skilled and experienced Technical Lead – AI/ML & Generative AI to lead the design, development, deployment, and scaling of enterprise-grade AI solutions.

The ideal candidate will have strong expertise in Machine Learning, Deep Learning, Generative AI, Agentic AI, MLOps, Data Engineering, and Cloud-Native AI Platforms.

The candidate will be responsible for leading AI initiatives, mentoring engineering teams, driving AI innovation, and delivering scalable AI products across business domains such as Financial Services, Lending, Customer Experience, Risk Analytics, Document Intelligence, and Intelligent Automation.

Key Responsibilities

AI Solution Architecture & Design

• Design scalable AI/ML architecture for enterprise applications.
• Lead AI platform strategy and technology roadmap.
• Define end-to-end AI solution architecture including:
• Data Ingestion
• Feature Engineering
• Model Training
• Model Deployment
• Model Monitoring
• Design AI-driven products using cloud-native architecture principles.
• Create reusable AI frameworks and accelerators.

Generative AI & Agentic AI

Lead implementation of:

• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Multi-Agent Systems
• Agentic AI Platforms
• Prompt Engineering Frameworks
• AI Workflow Automation

Machine Learning & Deep Learning

Design and develop:

• Classification Models
• Regression Models
• Recommendation Engines
• Forecasting Models
• Anomaly Detection Systems
• Computer Vision Solutions
• NLP Applications

Hands-on expertise in:

• Scikit-Learn
• TensorFlow
• PyTorch
• XGBoost
• LightGBM
• Hugging Face

RAG & Knowledge Systems

Architect enterprise-grade RAG solutions:

• Vector Databases
• Semantic Search
• Hybrid Search
• Knowledge Graphs
• Embedding Pipelines

Experience with:

• LangChain
• LangGraph
• LlamaIndex
• Haystack

Vector Databases:

• Pinecone
• ChromaDB
• Weaviate
• Milvus
• FAISS

MLOps & AI Platform Engineering

Lead AI platform deployment and governance:

• Model Lifecycle Management
• Model Registry
• Model Monitoring
• Drift Detection
• Feature Stores

Tools:

• MLflow
• Kubeflow
• Airflow
• SageMaker
• Vertex AI
• Databricks

Implement:

• CI/CD for AI Models
• Automated Training Pipelines
• Continuous Model Deployment

Cloud & Infrastructure

Architect AI workloads on:

• AWS
• Azure
• OCI
• GCP

Services:

• AWS Bedrock
• SageMaker
• EC2
• EKS
• Lambda
• S3

Containerization:

• Docker
• Kubernetes

Deployment Models:

• On-Premise
• Hybrid Cloud
• Multi-Cloud

AI Governance, Security & Compliance

Establish AI governance framework:

• Responsible AI
• Explainable AI (XAI)
• Model Auditing
• AI Risk Management

Leadership & Team Management

• Lead AI/ML engineering team.
• Mentor Data Scientists and AI Engineers.
• Conduct architecture reviews and code reviews.
• Drive best practices in AI engineering.
• Collaborate with Product Owners and Business Teams.
• Own end-to-end AI solution delivery.

Academic Qualification

• B.E. / B.Tech / MCA / M.Tech in Computer Science, AI, Data Science, Information Technology or related field.
• AI/ML certifications preferred.

Experience

• 8–15 years overall experience.
• Minimum 3–5 years leading AI/ML teams.
• Experience delivering production-grade AI solutions.
• Experience in Banking, NBFC, FinTech, Insurance or Financial Services preferred.