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AI Engineer - Generative AI & LLMs (AWS)
Overview / Summary We are seeking a highly skilled AI Engineer to design, develop, and deploy enterprise-scale AI solutions that solve complex business problems. This role focuses on Generative AI, Large Language Models (LLMs), Prompt Engineering, Agentic AI systems, Machine Learning, Data Science, and cloud-native engineering on AWS. The ideal candidate will build intelligent applications end-to-end and collaborate closely with cross-functional teams to deliver secure, scalable, and production-ready AI solutions aligned with enterprise standards.
Key Responsibilities - Design, develop, and deploy enterprise AI solutions using LLMs, Prompt Engineering, Agentic AI frameworks, Machine Learning, and Data Science techniques
- Build intelligent applications such as RAG systems, AI copilots, conversational assistants, agent workflows, document intelligence, and NLP applications
- Design and optimize prompts including templates, chaining strategies, structured outputs, and response optimization
- Develop and maintain data pipelines for structured and unstructured data supporting training, inference, analytics, and evaluation
- Implement retrieval pipelines, embeddings, vector search, tool calling, memory strategies, and orchestration for LLM applications
- Fine-tune, evaluate, optimize, and monitor AI/ML and LLM systems for performance, scalability, and cost efficiency
- Collaborate with stakeholders to translate business requirements into scalable AI solutions
- Build and manage AI infrastructure on AWS (e.g., S3, Lambda, EKS/ECS, API Gateway, IAM, CloudWatch, RDS, DynamoDB, OpenSearch, Bedrock)
- Provision infrastructure using Terraform/Scalr for secure, repeatable deployments
- Implement observability, monitoring, evaluation, feedback loops, and guardrails for AI systems
- Ensure solutions meet enterprise standards for security, compliance, and resiliency
- Lead technical design discussions, code reviews, and engineering best practices
- Support MLOps/LLMOps practices including CI/CD, versioning, testing, deployment, and incident response
- Communicate technical findings and risks to stakeholders and leadership
- Mentor junior engineers and contribute to reusable frameworks and standards
Required Qualifications - Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or related field
- 1+ years of experience in Python and software development for AI/ML, data engineering, or cloud applications
- 1+ years of experience in Machine Learning / Data Science including model development and deployment
- 1+ years of experience in LLMs / Generative AI including prompt engineering, RAG, embeddings, and evaluation frameworks
- Strong experience in Prompt Engineering (design patterns, chaining, structured outputs, prompt tuning)
- Strong understanding of Agentic AI workflows, orchestration, memory handling, and tool usage
- Experience with AWS for developing and deploying AI/ML solutions
- Experience with Terraform and/or Scalr for infrastructure provisioning
- Experience with APIs, microservices, and containerized environments
- Experience with SQL, NoSQL, vector databases, and data integration
- Strong knowledge of software engineering fundamentals (version control, CI/CD, testing, secure coding)
- Experience presenting technical concepts to stakeholders
- Strong analytical, problem-solving, and collaboration skills
