Develop and scale backend systems for autonomous AI agents, including multi-step reasoning, memory/state systems, RAG/retrieval pipelines, tool integration, observability, security compliance, and automated evaluation and monitoring for reliability and safety.
ROLE SUMMARY
The AI Acceleration (AIA) function within the Chief Marketing Office (CMO) is the single, business-led engine that owns the design, delivery, and scale-up of priority AI capabilities across Commercial. AIA works in tight collaboration with various Pfizer functions to deploy and maintain production-grade AI solutions that simplify how we work and drive measurable value across all processes.
As a Senior Associate, Backend Engineer, you will develop, and scale backend systems that power autonomous, tool‑using AI agents. This role focuses on building reliable, high‑performance services that enable multi‑step reasoning, planning, memory, retrieval, and tool integration across AI-driven workflows.
Basic Qualifications
Backend Engineering
System Design & Operations
Security & Compliance
Preferred Qualifications
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
Information & Business Tech
The AI Acceleration (AIA) function within the Chief Marketing Office (CMO) is the single, business-led engine that owns the design, delivery, and scale-up of priority AI capabilities across Commercial. AIA works in tight collaboration with various Pfizer functions to deploy and maintain production-grade AI solutions that simplify how we work and drive measurable value across all processes.
As a Senior Associate, Backend Engineer, you will develop, and scale backend systems that power autonomous, tool‑using AI agents. This role focuses on building reliable, high‑performance services that enable multi‑step reasoning, planning, memory, retrieval, and tool integration across AI-driven workflows.
- Build automated evaluation pipelines for agent reliability, accuracy, and safety
- Implement multi‑step reasoning, planning, and tool‑execution loops
- Deploy and maintain services using Docker, CI/CD, and cloud environments
- Ensure compliance with security, RBAC, and data protection requirements
- Develop state and memory systems for agent context and knowledge retention
- Optimize RAG pipelines and retrieval infrastructure
- Implement guardrails, validation layers, retry logic, and failure‑handling mechanisms
- Build automated evaluation pipelines for agent reliability, accuracy, and safety
- Implement multi‑step reasoning, planning, and tool‑execution loops
- Deploy and maintain services using Docker, CI/CD, and cloud environments
- Ensure compliance with security, RBAC, and data protection requirements
- Develop state and memory systems for agent context and knowledge retention
- Optimize RAG pipelines and retrieval infrastructure
- Implement guardrails, validation layers, retry logic, and failure‑handling mechanisms
- Develop monitoring for agent behavior, performance, cost, and decision paths
- Architect scalable, fault‑tolerant backend systems with observability and logging
- Build backend services supporting agentic and generative AI workflows
- Integrate LLMs with APIs, tools, databases, and external systems
Basic Qualifications
- Bachelor's or master's degree in computer science, or a related field (or equivalent experience).
- 2-5 years of experience in software engineering, data science, or related technical fields.
Backend Engineering
- Proficiency in Python
- Experience with FastAPI or Flask
- Knowledge of REST APIs, async processing, and distributed workers
- Experience with relational, NoSQL, and vector databases
System Design & Operations
- Hands-on experience with observability (logging, metrics, tracing)
- Proficiency with Docker, CI/CD pipelines, and cloud platforms
Security & Compliance
- Knowledge of API security, RBAC, and data handling best practices
- Experience working with PII and sensitive data
Preferred Qualifications
- Familiarity with LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks
- Understanding of tool-calling, structured outputs, and prompt reliability
- Experience with OpenAI/Azure OpenAI, Anthropic, Mistral, or open-source LLMs
- Experience with multi‑agent workflows
- Exposure to workflow orchestration tools (Airflow, Temporal, Dagster, Prefect)
- Familiarity with model serving frameworks (vLLM, Ray Serve, TGI, Modal)
- Understanding of AI safety, guardrails, and evaluation frameworks
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
Information & Business Tech
Top Skills
Metrics
Python,Fastapi,Flask,Rest Apis,Async Processing,Distributed Workers,Relational Databases,Nosql Databases,Vector Databases,Observability (Logging
Tracing),Docker,Ci/Cd,Cloud Platforms,Rbac,Langgraph,Langchain,Llamaindex,Crewai,Autogen,Openai,Azure Openai,Anthropic,Mistral,Vllm,Ray Serve,Tgi,Modal,Airflow,Temporal,Dagster,Prefect,Rag,Llms
Pfizer Chennai, Tamil Nadu, IND Office
Chennai, India
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