Senior GenAI Engineer

About the Role :

We are looking for a Senior GenAI Engineer with strong experience in building and delivering production-grade AI and Generative AI applications. The role involves designing end-to-end AI solutions, leading technical implementation, and mentoring teams while working closely with business and engineering stakeholders.

We are hiring for two domain-specific tracks :

- BFSI Track - AWS : Strong hands-on experience in BFSI/Banking/Financial Services along with AWS-based AI/GenAI deployments is mandatory.

- HCLS Track - Azure : Strong hands-on experience in Healthcare/Life Sciences (HCLS) along with Azure-based AI/GenAI deployments is mandatory.

Key Responsibilities :

- Lead the implementation and delivery of AI and Generative AI applications.

- Design end-to-end AI systems using commercial and open-source tools.

- Build and deploy LLM, RAG, and Agentic AI solutions for enterprise use cases.

- Translate business requirements into scalable AI-driven solutions.

- Collaborate with data engineering teams to ensure data quality, governance, and smooth data flows.

- Define reference architectures, technical roadmaps, and best practices for AI applications.

- Design and manage data ingestion pipelines, model training environments, CI/CD, and monitoring systems.

- Use cloud services and containerization to deploy and scale AI systems.

- Ensure scalability, reliability, security, and maintainability of AI solutions.

- Provide technical mentorship and conduct knowledge-sharing sessions.

Requirements :

- 4+ years of experience in AI, Machine Learning, GenAI, or related roles.

- Strong hands-on experience building AI agents using LangGraph, AutoGen, or CrewAI.

- Strong proficiency in Python and ML/DL frameworks such as TensorFlow, PyTorch, or Keras.

- Solid understanding of Deep Learning and NLP, including Transformers, RNN, CNN, and LSTM.

- Hands-on experience with RAG, LLMs, vector databases, prompt engineering, and Agentic AI.

- Strong experience with REST APIs, GraphQL, microservices, distributed systems, and event-driven architectures.

- Experience with message brokers such as Kafka or RabbitMQ.

Domain & Cloud Requirements - Mandatory :

BFSI Track - AWS :

- 2 - 3+ years of hands-on BFSI/Banking/Financial Services domain experience.

- Experience working on BFSI use cases such as banking, payments, lending, insurance, risk, fraud, wealth management, or financial operations.

- Strong hands-on experience with AWS for AI/GenAI deployments.

- Experience with services such as AWS Bedrock, SageMaker, OpenSearch, S3, Lambda, EKS/ECS, or equivalent AWS AI services is preferred.

HCLS Track - Azure :

- 2 - 3+ years of hands-on HCLS/Healthcare/Life Sciences domain experience.

- Experience working with healthcare providers, payers, health insurance, clinical, claims, or life sciences use cases.

- Strong hands-on experience with Microsoft Azure for AI/GenAI deployments.

- Experience with services such as Azure OpenAI, Azure AI Search, Azure ML, AKS, Azure Functions, and Azure Storage is preferred.

Good to Have :

- Docker, Kubernetes, and CI/CD tools such as Jenkins or GitLab.

- SQL and NoSQL databases such as PostgreSQL, MongoDB, or Cassandra.

- Infrastructure as Code using Terraform or CloudFormation.

- Hands-on experience with Hugging Face, OpenAI APIs, LLaMA, and other LLM platforms.

- Experience with MLOps / LLMOps, model training, fine-tuning, and model evaluation.

- Experience with monitoring and logging tools such as Prometheus, Grafana, or ELK.

- Experience deploying production-grade GenAI/Agentic AI applications at enterprise scale.