Requirement/Must Have:
1+ years of experience in ML, NLP, AI system design with 1-2 years in Gen AI or Agentic AI.
Extensive hands-on experience with Amazon Bedrock, Agent Core Platform, AWS Strands, SageMaker, S3, Lambda, API Gateway, SQS/SNS, and other core AWS services like Redshift, Aurora Postgres, Glue, EMR, Lambda, Step Functions, CloudWatch.
Practical experience with foundational models (e.g., Anthropic Claude, Stability AI, Llama variants), including prompt engineering, fine-tuning, and safety mechanisms.
Advanced proficiency in Python and its data science stack (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow).
Familiarity with vector databases such as Pinecone, Weaviate, OpenSearch, or RDS Vector Store for RAG implementations.
Proven experience with orchestration tools like LangChain and LlamaIndex for building autonomous agents.
Responsibilities:
Develop MVP User Stories (Re-usable components/etc.).
Support backlog creation, prioritization, and Story mapping.
Support in technical design and solutioning.
Ability to work across tiers – APIs, databases (basic developer tasks).
Ability to utilize DevOps CI/CD pipeline, create/configure build and deploy jobs.
Experience working in XP and pair programming model and understands and performs TDD.
Responsible for assigned task delivery and quality and knowledge transfer through daily pairing.
Must be able to clearly communicate with team members and leadership.
Participate in paired programming and XP development.
Strong ability to work independently when required.
Turn complex ideas into manageable pieces of work.
Hands-on, individual contribution and mentor other developers in team.
Support team members on troubleshooting.
Nice to Have:
Proficient in Terraform and Terraform Enterprise for scalable, automated infrastructure provisioning.
Experienced with Concourse and GitHub Actions for continuous integration and deployment workflows.
Hands-on experience with Apache Iceberg and a strong understanding of medallion architecture principles.
Skilled in building and optimizing Data Lakehouse solutions using open table formats to enhance performance and scalability.