AI Engineer - Python

Cognizant; Pune District, Chennai District, Bengaluru; Hybrid; INR 2,500,000 - 4,500,000; Full time

Job summary

Cognizant in Pune, India seeks a Senior AI Engineer to advance Applied AI capabilities. You will build stateful agent orchestration, robust data pipelines, and scalable backend services for high-velocity AI applications.

You’ll own memory, data retrieval, and production reliability, collaborating with product teams and governance to ensure security, privacy and cost efficiency. Strong Python and LLM experience are essential.

Qualifications

• BS/MS in Computer Science or related field or equivalent experience.
• Hands-on software engineering for backend services, APIs or data-intensive apps.
• Strong foundations in algorithms, data structures and systems.
• Exposure to LLM concepts: retrieval, grounding, prompts, agents.
• Experience with design, reviews, testing and operational playbooks for reliability.
• Proficiency with modern software delivery practices, version control, CI/CD and observability.
• Familiarity with cloud-native services and containerization.
• Strong written and verbal communication, and collaboration with product teams.
• Ability to ship quickly in fast-evolving tech areas with incomplete information.
• Senior level: ownership of services/end-to-end delivery and reliability initiatives.

Responsibilities

• Build features and services across AI stack orchestration, retrieval, grounding prompts and agent logic.
• Implement evaluation, guardrails, serving and observability.
• Develop robust data processing and integration pipelines for high-quality AI apps and analytics.
• Contribute to design docs, code reviews, testing and operational playbooks for reliability.
• Partner with product and business stakeholders to define requirements and measure outcomes.
• Instrument telemetry and evaluation to monitor quality, safety, latency and cost.

Skills

Python

LLM applications

Backend development

Cloud & containers

Observability & CICD

Data structures & algorithms

Team collaboration

On-call reliability

Memory architectures

Communication

Education

BS/MS in Computer Science

Tools

Git

CI/CD

Containerization

Vector databases

Job description

Responsibilities

• Build features and services across the AI stack orchestration retrieval/grounding prompt/agent logic
• evaluation/guardrails serving and observability
• Implement robust data processing and integration pipelines to enable high quality AI applications and analytics
• Contribute to design docs code reviews testing and operational playbooks to ensure reliability maintainability
• and resilience
• Partner with product and business stakeholders to define requirements iterate quickly and measure outcomes
• using clear success metrics
• Instrument telemetry and evaluation to monitor quality safety latency and cost improve performance
• based on data
• Follow responsible AI practices for security privacy compliance and safety in collaboration with governance
• teams
• Participate in on call and incident response rotations as appropriate drive post incident improvements
• Share learnings via demos and documentation contribute to AI literacy and enablement across the org

Qualifications

• BS/MS in Computer Science or a related field or equivalent experience
• Practical software engineering experience building backend services APIs or data intensive applications
• strong foundations in algorithms data structures and systems
• Exposure to or handson experience with LLM application concepts such as retrieval grounding prompt agent
• design functiontool use evaluation safety guardrails and costlatency optimization
• Proficiency with modern software delivery practices version control CICD testing observability familiarity
• with cloud native services and containerization
• Ability to collaborate with product and business partners strong written and verbal communication skills
• Bias to ship learn and iterate comfortable working in fast evolving technology areas with incomplete
• information
• For Senior level demonstrated ownership of services or platform components endtoend delivery of crossservice
• initiatives and contributions to reliabilitySLOs and operational excellence

This is the sumary

Senior AI Engineer Applied AI Technical Competencies

1 Agentic Workflows Memory Systems

Stateful Orchestration Building and debugging productiongrade cyclic multiagent workflows and state machines

Context Memory Engineering Implementing multilayered memory architectures including shortterm memory for active turn execution longterm memory for crosssession state persistence and episodic summarization to manage token context windows

Tool Call Management Designing dependable functioncalling patterns equipped with automated retry logic and selfcorrection handlers

2 Data Retrieval Infrastructure

Vector Relational Storage Managing relational metadata schemas and executing optimized semantic vector similarity searches inside a combined relational database layer

Document Persistence Utilizing documentstore databases to store unstructured execution payloads dynamic agent states and raw chat logs

Hybrid RAG Pipelines Combining relationalexactmatch queries with vectorspace searches for highprecision retrieval

3 Production Reliability Performance

Granular Tracing Instrumenting endtoend tracing to monitor agent execution steps debug nondeterministic loops and track token costs

Automated Evals Creating programmatic evaluation testing and scoring frameworks to benchmark agent accuracy before production deployment

Core Backend Development Writing clean concurrent asynchronous Python code to handle high throughput foundation model APIs