GenAI Python - Senior Engineer

Job Description

Key Responsibilities:

GenAI Application Development
•    Build, optimize, and maintain generative AI applications using Python, FastAPI, and modern microservices patterns.
•    Integrate AWS Bedrock foundation models and embeddings into enterprise workflows.
•    Develop scalable, secure REST APIs to expose GenAI capabilities.
AWS Cloud Engineering
•    Design and implement serverless, event-driven AI workflows using AWS Lambda, Step Functions, API Gateway, SQS/SNS, and EventBridge.
•    Build and optimize data persistence layers using AWS RDS (PostgreSQL/MySQL).
AI/ML Pipeline Enablement
•    Implement prompt engineering, model orchestration, and inference pipelines.
•    Fine-tune and evaluate LLMs using Bedrock or other supported frameworks.
•    Collaborate with Data Science teams to deploy custom models into AWS environments.
System Architecture & Best Practices
•    Contribute to architecture designs for GenAI microservices and data flows.
•    Ensure adherence to security, compliance, and cost-optimization best practices in AWS.
•    Implement robust monitoring, logging, and observability for AI services.
Collaboration & Stakeholder Engagement
•    Work with product managers, data engineers, cloud architects, and UX teams to translate requirements into scalable AI features.
•    Document services, workflows, APIs, and operational runbooks.
Innovation & Continuous Improvement
•    Evaluate new LLMs, embeddings, vector databases, and prompt orchestration tools.
•    Explore advanced Python capabilities and emerging GenAI frameworks.
•    Champion experimentation and rapid prototyping of AI-driven features.
Basic Qualifications:
•    Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or related field.
•    5+ years of hands-on software engineering, with at least 3 years in AI/LLM-focused development.
•    Expert-level proficiency in Python (async programming, advanced OOP, design patterns).
•    Strong experience with FastAPI and REST API development.
•    Hands-on expertise with AWS Lambda, Bedrock, Step Functions, RDS, S3, IAM, and CloudWatch.
•    Proven experience building production-grade GenAI applications or LLM-integrated solutions.
•    Familiarity with vector databases (FAISS, Pinecone, or AWS OpenSearch vectors).
•    Solid understanding of CI/CD, DevOps, and GitOps workflows.
Preferred Qualifications
•    Experience with LangChain or Bedrock Agents.
•    Knowledge of RAG architecture and embedding pipelines.
•    Experience with AWS SageMaker.
•    Strong knowledge of containerized deployment (Docker).
•    Experience optimizing high-performance Python applications.
•    Exposure to MLOps and model evaluation metrics.
•    Open-source contributions in AI or Python ecosystems.

Mandatory Competencies