Design and deploy generative AI and machine learning solutions across AWS, Azure, and Databricks environments.
Collaborate with data scientists, engineers, product managers, and business stakeholders to deliver impactful AI solutions.
Build production applications using Amazon Bedrock models such as Claude, Titan, Llama, and Mistral.
Develop AI agents using Bedrock Agents, action groups, guardrails, and Prompt Flow orchestration.
Design prompt engineering strategies, evaluation frameworks, and responsible AI controls including filtering and bias detection.
Design scalable retrieval augmented generation architectures.
Implement vector search using OpenSearch Serverless and pgvector with Aurora PostgreSQL or Amazon RDS.
Develop embedding pipelines, chunking strategies, hybrid search, re ranking, and metadata filtering.
Build serverless AI systems using Lambda, API Gateway, Step Functions, and EventBridge.
Develop ML pipelines using SageMaker, Feature Store, and SageMaker Pipelines.
Design data pipelines using Glue, Athena, and Redshift.
Implement secure VPC architectures and infrastructure as code using AWS CDK or CloudFormation.
Create CI/CD pipelines using GitHub Actions.
Implement model testing, monitoring, versioning, and deployment strategies.
Build alerting and incident response for ML pipelines.

Bachelor’s degree in Computer Science, Machine Learning, Data Science, Mathematics, or related field.
5+ years in machine learning, data engineering, or software engineering.
3+ years working with cloud platforms such as AWS, Azure, or Databricks.
2+ years working with generative AI and large language models.
Experience deploying ML systems in production and building RAG systems with vector databases.
Strong Python and SQL skills.
Experience with PyTorch, TensorFlow, or Hugging Face.
Familiar with LangChain, LlamaIndex, or Semantic Kernel.
Experience building APIs using FastAPI, Flask, or Django.
Knowledge of Docker and CI/CD tools.
Preferred AWS Solutions Architect certification.
Experience with conversational AI, document processing, recommendation systems, NLP, computer vision, or time series.

Senior Software Engineer – AI/ML

Key skills