Senior Software Engineer - Python

About the role

Devsinc is hiring a Senior Software Engineer in Python in Lahore. The role covers designing, building and scaling backend services and APIs, and shipping agentic AI systems such as multi-step agents, tool calling, MCP integrations and orchestration. It also involves building RAG pipelines, integrating LLMs, setting up evaluation and guardrails, deploying on cloud platforms, and leading technical design and mentoring engineers.

Key responsibilities

• Design, build and scale backend services and APIs using Python with FastAPI, Django and Flask
• Build and ship agentic AI systems (multi-step agents, tool calling, MCP integrations, orchestration with LangChain/LangGraph, LlamaIndex, CrewAI or the Claude Agent SDK)
• Develop RAG pipelines: document ingestion, chunking, embeddings, vector databases, retrieval tuning and evaluation
• Integrate and optimise LLMs (OpenAI, Anthropic Claude, Gemini, open-source models) for accuracy, latency and cost
• Build data pipelines, analytics and ML workflows with Pandas, NumPy, scikit-learn and PyTorch or TensorFlow
• Set up LLM evaluation, guardrails, monitoring and observability (LangSmith, Langfuse or similar) for production AI systems
• Deploy and operate services on AWS, GCP or Azure with Docker, Kubernetes and CI/CD pipelines
• Lead technical design, break down work, mentor engineers and set code-quality and AI-engineering standards
• Present AI solutions, demos and technical roadmaps to clients, stakeholders and leadership
• Take part in on-call rotations and production incident response

Required profile

• 3 to 6 years of professional software engineering experience, mostly in Python
• Strong production experience with FastAPI plus Django and/or Flask, including async programming and REST API design
• Hands-on experience building LLM-powered applications, including at least one RAG or agent-based system in production
• Proven ability to lead projects and guide team members from proof of concept to production
• Excellent communication skills, able to explain complex AI concepts simply and represent the technical approach to clients
• Nice to have: experience with fine-tuning, prompt optimization or model distillation; MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, Bedrock); big data or streaming tools (Spark, Airflow, Kafka, dbt); Node.js or TypeScript; published projects, Kaggle work or open-source contributions in AI/ML; AWS, GCP or Azure AI or ML certifications

Required skills

• Vector databases (Pinecone, Weaviate, Qdrant, pgvector) and embedding models
• SQL (PostgreSQL) and NoSQL stores and Redis
• Cloud (AWS, GCP or Azure) and Docker
• Testing with pytest and clean, typed Python (type hints, Pydantic)
• API security, OAuth 2.0, JWT and secure handling of sensitive data