Senior Software Engineer - Python

We are seeking a skilled software engineer with extensive experience in Python to design, build, and scale backend services and APIs. The ideal candidate will work on cutting-edge AI systems, including multi-step agents, tool integrations, and orchestration frameworks. This role involves developing retrieval-augmented generation (RAG) pipelines, optimizing large language models (LLMs) for performance and cost, and building robust data pipelines and machine learning workflows. You will deploy and operate services on cloud platforms while leading technical design, mentoring engineers, and presenting AI solutions to stakeholders.

Key Responsibilities

- Design, develop, and scale backend services and APIs using Python frameworks such as FastAPI, Django, and Flask.
- Build and deploy agentic AI systems, including multi-step agents, tool calling, MCP integrations, and orchestration using frameworks like LangChain, LangGraph, LlamaIndex, CrewAI, or Claude Agent SDK.
- Develop RAG pipelines involving document ingestion, chunking, embeddings, vector databases, retrieval tuning, and evaluation.
- Integrate and optimize LLMs from providers like OpenAI, Anthropic Claude, Gemini, and open-source models to enhance accuracy, latency, and cost efficiency.
- Construct data pipelines, analytics, and machine learning workflows using libraries such as Pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
- Establish LLM evaluation, guardrails, monitoring, and observability for production AI systems using tools like LangSmith or Langfuse.
- Deploy and maintain services on cloud platforms (AWS, GCP, Azure) using Docker, Kubernetes, and CI/CD pipelines.
- Lead technical design discussions, break down complex tasks, mentor junior engineers, and enforce code quality and AI engineering standards.
- Present AI solutions, conduct demos, and communicate technical roadmaps to clients, stakeholders, and leadership teams.
- Participate in on-call rotations and manage production incident responses.

Required Qualifications

- 3 to 6 years of professional software engineering experience, primarily with Python.
- Strong production experience with FastAPI, along with Django and/or Flask, including asynchronous programming and REST API design.
- Proven hands-on experience building LLM-powered applications, including at least one RAG or agent-based system deployed in production.
- Working knowledge of vector databases such as Pinecone, Weaviate, Qdrant, or pgvector, and embedding models.
- Solid understanding of data science fundamentals including data wrangling, statistics, model evaluation, and handling both structured and unstructured data.
- Proficiency in SQL (PostgreSQL) and experience with NoSQL databases and Redis.
- Practical cloud experience with AWS, GCP, or Azure, and containerization using Docker.
- Strong testing practices using pytest and writing clean, typed Python code with type hints and Pydantic.
- Understanding of API security protocols, including OAuth 2.0, JWT, and responsible management of sensitive data.
- Excellent communication skills with the ability to simplify complex AI concepts, lead client demos, and effectively represent the technical approach.
- Demonstrated ability to lead projects and guide teams from proof of concept through to production delivery.
- Curiosity and adaptability to quickly evaluate and adopt new AI tools and models.

Preferred Qualifications and Benefits

- Experience with fine-tuning, prompt optimization, or model distillation techniques.
- Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Bedrock.
- Experience building MCP servers or multi-agent systems.
- Knowledge of big data or streaming technologies like Spark, Airflow, Kafka, or dbt.
- Exposure to Node.js or TypeScript for full-stack collaboration.
- Contributions to published projects, research, Kaggle competitions, or open-source AI/ML initiatives.
- Professional certifications in AI or ML from AWS, GCP, or Azure.

This role offers the opportunity to work on innovative AI technologies in a collaborative environment, with a focus on technical leadership and delivering impactful solutions.