Cognizant is looking for a hands-on Technical Lead to architect and deploy agentic AI systems that solve real-world problems within the aviation sector. This is a high-ownership role where you will bridge the gap between complex business requirements and cutting-edge production-grade AI.
The Role: What You Will Actually Do
You aren’t just writing code in a silo. As a Forward Deployed AI Engineer, you will embed yourself directly with business stakeholders to understand their pain points before building the solution. You are the architect, the developer, and the owner of the end-to-end outcome.
Your daily routine involves designing RAG pipelines, connecting AI agents to enterprise APIs, and ensuring that every system you build is secure, scalable, and reliable. You’ll be working on a “paved road” infrastructure, meaning you have the tools to self-serve against systems like Etihad’s, but you have the autonomy to make the key architectural decisions that define the squad’s success.
Core Responsibilities
- Own the Outcome: Take full ownership of specific domain results, from discovery to deployment.
- Build Agentic Systems: Default to agentic coding. Build agents that can reason, call tools, handle exceptions, and work with humans in the loop.
- Technical Leadership: Set the bar for quality, testing, observability, and security across the squad.
- Mentor and Grow: As a lead, you will review code and help junior engineers improve their output in security, latency, and cost-efficiency.
- Infrastructure Integration: Use MCP-based integrations to link agents to backend systems using REST/OpenAPI, webhooks, and event-driven patterns.
Technical Requirements & Eligibility
This position is tailored for seasoned engineers who have transitioned into the world of applied Generative AI. You should be comfortable balancing high-level architecture with deep-dive technical troubleshooting.
- Experience: 8+ years in production-grade software development, with at least 4 years focused on GenAI, LLMs, and applied ML.
- Agentic Expertise: A minimum of 1 year of hands-on experience as an early adopter of agentic AI frameworks (e.g., LangGraph, CrewAI, or AutoGen).
- Programming Stack: Strong Python proficiency is non-negotiable. You should also be comfortable with at least one of these: TypeScript, JavaScript, Java, or C#.
- Infrastructure: Proficiency with cloud-based deployments, containerization, and vector databases like Pinecone, Weaviate, or Azure AI Search.
- Mindset: A business-first approach. You need to be able to talk to non-technical stakeholders and decide when AI is (and isn’t) the right tool for the job.
Why This Matters
This is an opportunity to move beyond basic API wrappers. You will be building multi-agent systems and evaluation frameworks in a complex, operations-heavy industry. If you have a background in logistics, aviation, or supply chain, your profile will stand out. This role is a direct pathway to becoming an AI Value Architect, putting you at the center of how large-scale enterprises integrate AI into their DNA.
How to Apply
Cognizant manages its recruitment through its internal platform. To view the full job description or submit your application, visit the official application page linked below. Ensure your resume highlights your experience with agentic frameworks and complex system integrations to improve your chances.
Click here to visit the application page
Frequently Asked Questions (FAQ)
What is the primary focus of this role?
The role focuses on building and deploying enterprise-grade agentic AI systems that solve specific business problems, primarily within the aviation industry, while setting the technical direction for an embedded squad.
Is this a remote role?
The role involves embedding with stakeholders, so it requires a high degree of collaboration and presence. Check the specific location details on the application page for the most current information regarding site requirements.
What experience level is required for this position?
This is a senior-level position requiring 8+ years of total software engineering experience, including significant hands-on work with LLMs and agentic AI frameworks.