Senior Associate, Core Technology

As a Senior Associate, Core Technology, you’ll leverage your technical depth and problem-solving skills to build reliable, lightweight, high-performing web applications and platform services. While your strength is back-end development (Python/Django and related frameworks), you’re comfortable collaborating across the stack and are conversant with modern front-end ecosystems (React/Angular/Vue). You thrive in an agile, sprint-driven environment and bring a strong engineering mindset: clean architecture, test-driven development, automated testing, CI/CD, and scalable system design. You’re also excited by the evolution of AI engineering - especially RAG (Retrieval-Augmented Generation), LLM integrations, and agentic workflows. You can take a problem from ambiguity to delivery—design → build → test → deploy → iterate.

Responsibilities

Design: Create technical designs (HLD/LLD) for new capabilities and improvements, ensuring solutions are scalable, secure, and maintainable; Backend engineering (Python): Build and enhance backend services and APIs primarily in Python/Django (and related frameworks as needed), focusing on performance, reliability, and clean architecture; Database & data layer: Work with relational databases (e.g., PostgreSQL/Redshift) and support data modeling, query optimization, and production readiness; AI/RAG & Agent work: Design and implement custom RAG workflows and LLM integrations—covering retrieval, prompt orchestration, grounding, and connecting to vector stores (e.g., Pinecone/FAISS) where applicable; Data pipelines: Contribute to building/operating data pipelines and jobs using AWS and open-source tools (e.g., EMR/Glue/Redshift, Airflow/Spark)—including orchestration, monitoring, and reliability improvements; Engineering excellence: Write code that holds up in TDD, build automated tests, participate in reviews, and support CI/CD practices using tools like GitHub and JIRA; Sprint ownership & leadership: Independently run sprints for a small team—planning, task breakdown, execution tracking, and clear communication with internal stakeholders and clients

Requirements

4–7 years of strong experience in Python, with deep expertise in Django and other frameworks; Strong backend foundation and familiarity with frameworks such as Django / Flask / Pyramid (or equivalents); Solid experience working with AWS (or similar cloud platforms) in production environments; Strong understanding of: HLD/LLD, system design fundamentals, API design, and scalable architectures; Engineering best practices: testing, code quality, documentation, and maintainability; Hands-on experience building AI/LLM solutions, including: RAG pipelines and agent workflows; Tools/frameworks such as LangChain, Pydantic, and related ecosystems; Familiarity with AI agent design patterns and best practices