Senior Software Engineer - Gen AI

Your Team's Impact

We are looking for a Senior Software Engineer who is passionate about Generative AI, Agentic systems, and cloud-native API development. In this role, you will be a key contributor in designing, building, and deploying production-grade AI-powered applications and intelligent agent frameworks that transform the way our products and customers interact with data and automation.

You will collaborate closely with ML Engineers, Data Scientists, Product Managers, and Cloud Architects to deliver scalable, reliable, and innovative solutions powered by cutting-edge GenAI technologies.

What You'll Do

GenAI & Agentic Development

• Design and develop Agentic AI workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar
• Build and integrate LLM-powered applications using models from OpenAI, Anthropic, Meta (LLaMA), Mistral, or foundation models on cloud platforms
• Implement Retrieval-Augmented Generation (RAG) pipelines, vector stores, and semantic search capabilities
• Develop multi-agent orchestration systems with defined tool use, memory management, and reasoning loops
• Evaluate, fine-tune, and optimize LLM behavior through prompt engineering and chain-of-thought design
  

API Development & Backend Engineering

• Build high-performance, scalable RESTful APIs and async microservices using FastAPI and Python
• Design clean, modular, and well-documented API contracts following OpenAPI/Swagger standards
• Implement authentication, authorization, rate limiting, and security best practices across APIs
• Develop event-driven and streaming architectures to support real-time AI inference pipelines

Cloud & Platform Engineering

• Deploy and manage AI workloads on AWS (SageMaker, Lambda, API Gateway, Bedrock, S3, ECS/EKS)
• Utilize Databricks for large-scale data processing, MLflow model tracking, and AI/ML pipeline orchestration
• Build CI/CD pipelines and infrastructure-as-code (IaC) using tools like Terraform, AWS CDK, or similar
• Ensure scalability, observability, and reliability through cloud-native monitoring and logging practices

Engineering Excellence

• Write clean, testable, production-ready Python code following software engineering best practices
• Conduct code reviews and mentor junior engineers on GenAI patterns and best practices
• Contribute to architectural decisions, technical roadmaps, and engineering documentation
• Stay current with the rapidly evolving GenAI ecosystem and champion the adoption of emerging tools
  

What We're Looking For

• 57 years of professional software engineering experience
• Hands-on Python development in production environments
• Experience with GenAI technologies including LLMs, RAG, embeddings, or prompt engineering
• Building and deploying APIs using FastAPI or similar async Python frameworks
• Experience working with AWS cloud services in a production environment
• Hands-on experience with Databricks for data/AI workloads

Python & Frameworks

• Expert-level Python (async programming, type hints, Pydantic, dependency injection)
• FastAPI – routing, middleware, background tasks, OpenAPI spec generation
• Experience with SQLAlchemy, Alembic, or async ORMs
• Unit/integration testing with pytest, pytest-asyncio

GenAI & Agentic

• Strong understanding of LLM internals, tokenization, context windows, and model behavior
• Experience with LangChain / LangGraph / AutoGen / CrewAI or similar agentic frameworks
• Familiarity with vector databases – Pinecone, Weaviate, pgvector, ChromaDB, or FAISS
• Knowledge of RAG architectures, chunking strategies, and embedding models
• Hands-on experience with OpenAI API, Anthropic Claude API, AWS Bedrock, or Hugging Face models

Cloud – AWS

• AWS Bedrock – LLM model invocation and management
• AWS Lambda, API Gateway, ECS/EKS – serverless and containerized deployments
• S3, DynamoDB, RDS/Aurora – data storage patterns
• IAM, VPC, Secrets Manager – security and access control
• Familiarity with AWS CDK or CloudFormation

Databricks

• Experience with Databricks Workflows, Delta Lake, Unity Catalog
• Familiarity with MLflow for experiment tracking and model registry
• Using Databricks for AI/BI or LLM serving pipelines

General Engineering

• Docker & Kubernetes – containerization and orchestration
• Git – branching strategies, PR workflows, GitOps
• CI/CD – GitHub Actions, GitLab CI, Jenkins, or similar
• Understanding of distributed systems, event streaming (Kafka or AWS Kinesis), and microservice patterns

Preferred / Nice-to-Have Qualifications

• Experience with multi-modal AI (vision + language models)
• Familiarity with Azure OpenAI Service or Google Vertex AI
• Exposure to Terraform or Pulumi for infrastructure automation
• Contributions to open-source AI/ML projects
• Experience with GraphQL APIs
• Background in data engineering or MLOps pipelines
• AWS Certifications (Solutions Architect, ML Specialty)
• Databricks Certified Associate or Professional badge

Education

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical field
• Equivalent practical experience and demonstrable project portfolio will be considered.