We are looking for a seasoned Senior Python Engineer with 9+ years of hands-on experience building robust, scalable, and cloud-native systems. The ideal candidate is a technical leader who thrives in microservices environments, has deep expertise with Python frameworks such as Django and Celery, and brings strong database intuition. Exposure to Agentic AI and the ability to leverage it in product development is a significant advantage.
Key Responsibilities
▸ Django & Celery. Design, develop, and maintain high-performance Python-based backend services using
▸ cloud-native applications-Architect and build
– Deploy and manage services on AWS / GCP / Azure
– Design for scalability, fault tolerance, and observability
▸ microservice architectures Lead the design and evolution of
– Define service boundaries, APIs, and inter-service communication patterns
– Ensure reliable deployments using container orchestration
▸ database design and performance tuning-Drive
– Optimize complex SQL queries and indexes across PostgreSQL / MySQL
– Conduct query profiling, execution plan analysis, and schema reviews
▸ Agentic AI capabilities-Collaborate with product teams to integrate
– Build AI-powered workflows using LLM orchestration frameworks
– Contribute to product features driven by multi-agent pipelines
▸ Mentor junior engineers, lead code reviews, and uphold engineering best practices.
▸ Participate in system design discussions, technical planning, and roadmap execution.
Required Skills & Qualifications
Core Engineering
▸ 10+ years of professional software engineering experience.
▸ Python (3.8+)Expert-level proficiency in
▸ Django (DRF, ORM, middleware, signals)Deep hands-on experience with
▸ Celery Strong experience with
– Task queues, scheduling, retry strategies, beat scheduler
– Broker configuration with Redis or RabbitMQ
Cloud & Infrastructure
▸ cloud-native applications Proven experience building and operating
– Proficient with at least one major cloud provider: AWS, GCP, or Azure
– Familiar with cloud-native patterns: managed queues, blob storage, autoscaling, secrets management
▸ Docker and container lifecycle management Strong grasp of
▸ Experience with CI/CD pipelines — GitHub Actions, GitLab CI, ArgoCD, or similar.
Microservices & Architecture
▸ microservice architectures Solid experience designing and operating
▸ Familiar with synchronous (REST, gRPC) and asynchronous (Kafka, SQS, RabbitMQ) communication patterns.
▸ Understanding of API gateway patterns, service meshes, and distributed tracing.
▸ Experience with event-driven architecture and CQRS patterns is a plus.
Databases
▸ RDBMS (PostgreSQL preferred, MySQL accepted)Strong experience with
▸ query tuning and performance optimization Expert in
– EXPLAIN / EXPLAIN ANALYZE, index strategy, covering indexes, partial indexes
– Connection pooling (PgBouncer, RDS Proxy), read replicas
▸ Experience with schema migrations and managing DB changes in production safely.
▸ Working knowledge of NoSQL (Redis, MongoDB, Elasticsearch) as a complement to RDBMS.
Good to Have
▸ Agentic AI into commercial products Experience building or integrating
– Hands-on work with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks
– Designing multi-agent workflows, tool-use patterns, and prompt engineering
– Integrating LLM APIs (OpenAI, Anthropic, Gemini, open-source models)
▸ Familiarity with vector databases (Pinecone, Weaviate, pgvector) for RAG pipelines.
▸ Experience with ML model serving and integration (FastAPI, Triton, etc.).
▸ Contributions to open-source projects or published technical writing.
What We Value
▸ Strong sense of ownership and accountability for delivered systems.
▸ Excellent communication skills — can translate technical complexity to non-technical stakeholders.
▸ Collaborative team player who gives and receives constructive feedback gracefully.
▸ Curious, self-directed learner who keeps up with the evolving engineering landscape.
▸ Comfortable operating in ambiguous, fast-moving product environments.