AI Engineer

We are seeking an experienced AI Engineer specializing in Agentic AI frameworks and Generative AI technologies to design and deliver end-to-end, enterprise-grade AI solutions. This is a consultative, client-facing role that combines deep technical expertise with the ability to identify high-value use cases, articulate business impact, and implement scalable, production-ready AI systems.

You will work closely with clients, product managers, and cross-functional teams to build autonomous agents, multi-agent workflows, and GenAI-powered solutions across cloud platforms, with a strong focus on Microsoft and Azure-based AI ecosystems.

Responsibilities

• Design and implement Agentic AI architectures for complex enterprise workflows

• Develop and deploy autonomous and multi-agent systems with planning, reasoning, memory persistence, and secure tool execution

• Integrate Generative AI capabilities (LLMs and multimodal models) into client solutions

• Deliver end-to-end AI solutions, from ideation and use-case discovery through production deployment

• Build, fine-tune, and evaluate LLM-based Q&A and RAG solutions using frameworks such as AWS Bedrock, LangGraph, HuggingFace Transformers, or OpenAI APIs

• Design prompt templates, retrieval strategies, and evaluation approaches to improve accuracy, factuality, and performance

• Create and support data pipelines for training, testing, annotation, and evaluation

• Extend Microsoft 365 Copilot by building custom plugins and declarative agents using Microsoft Copilot Studio, surfacing enterprise data in Teams and Office applications

• Operationalize AI solutions using Microsoft AI Foundry, including model lifecycle management, Prompt Flow evaluation, and governance

• Architect scalable deployments using Azure Container Apps, Azure Kubernetes Service (AKS), or Azure Functions

• Collaborate with product managers to translate user and business requirements into technical features

• Engage with clients to identify impactful AI use cases, define business benefits, and support AI strategy alignment

• Conduct workshops, assessments, and executive-level discussions on AI adoption and emerging trends

• Ensure compliance with AI ethics, security, privacy, and governance standards

• Develop reusable accelerators, frameworks, and best practices for Agentic AI and GenAI

• Mentor junior engineers and guide cross-functional delivery teams

Bachelor's or Master's degree in Computer Science, AI/ML, or a related field (or equivalent practical experience)

• 8-12 years of overall experience, including 3-4+ years in AI solution delivery and client-facing consulting roles

• Strong hands-on experience with Agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI)

• Deep expertise in Generative AI, including prompt engineering, fine-tuning, and evaluation

• Proficiency in Python and familiarity with NLP/deep learning libraries (PyTorch, TensorFlow, scikit-learn, HuggingFace Transformers)

• Experience building Q&A systems and RAG pipelines

• Knowledge of vector databases and semantic search concepts

• Experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, or GCP Vertex AI

• Strong understanding of MLOps / LLMOps practices and deployment pipelines

• Experience with FastAPI, Flask, or Django for production-grade APIs

• Proficiency in SQL and NoSQL databases, including data modeling for AI metadata

• Experience deploying AI workloads using Azure Container Apps, AKS, or serverless architectures

• Hands-on experience with Microsoft Copilot Studio, Power Platform connectors, and custom copilots

• Experience implementing Azure AI Search (vector, semantic, hybrid search) and Microsoft Fabric/OneLake

• Ability to clearly articulate business value and engage in client-facing discussions

• Experience with Git and collaborative, cloud-based development workflows

Nice to Have

• Microsoft Certified: Azure AI Engineer Associate or similar Azure OpenAI certifications

• Experience with enterprise-grade security (Managed Identities, Private Endpoints, Content Safety filters)

• Familiarity with agent tracing, token usage monitoring, and observability using Azure Monitor / Application Insights

• Knowledge of Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols

• Experience designing interoperable, cross-vendor agent ecosystems

A competitive salary based on your qualities and experience

• NS business card to cover your commute expenses

• 25 days of paid holiday per year

• A laptop and a smartphone

• A pension scheme

• Health insurance

• Organization driven by technology - we have a tremendous technology backbone

• Access to Udemy, Cognizant Academy digital libraries for your continuous learning

• Open, 'can do' team spirit and international environment that encourages making your ideas reality!

Diversity and Inclusion at Cognizant