Gen AI Solutions Engineer

**Job Title:** Gen AI Solutions Engineer

**Client:** Conduent

**Skill Level:** C07

**Number of Positions:** 3

**Work Location:** Bangalore / Hyderabad / Noida

**Work Mode:** Hybrid – 3 days in office

**Maximum Budget:** 30 LPA

**Communication:** Excellent

Job Description

**Experience and Technical Requirements**

• 10+ years of experience in software/cloud engineering, AI, data engineering, or application development.

• 3+ years serving as a Lead Developer on enterprise projects, developing and delivering cloud-native applications and services.

• Experience delivering enterprise AI or GenAI solutions into production environments.

• Hands-on expertise in developing and deploying applications on Azure, including App Service, Azure Functions, Container Apps, Azure AI Foundry, AKS, Storage, Key Vault, API Management, or similar components.

• Hands-on experience delivering GenAI solutions into production environments, including prompt and RAG (Retrieval-Augmented Generation) patterns, responsible AI controls and guardrails, AI orchestration, AI/ML model lifecycle management, and secure integration of AI capabilities into analytics and enterprise applications.

• Strong Python development skills.

• Experience building REST APIs, microservices, and implementing cloud-native applications.

• Strong understanding of software architecture principles and design patterns.

• Experience building containerized applications using Docker and Kubernetes.

• BS or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.

Mandatory Supplier Screening Requirement

The supplier must conduct the first round of interviews to evaluate candidates and share the interview feedback along with each resume submitted to Conduent.

Agentic AI Screening

Ask the candidate:

**“Describe one Agentic workflow you implemented.”**

A strong candidate should be able to explain the following agents:

• Planner Agent

• Retriever Agent

• Validator Agent

• Critic Agent

• Supervisor Agent

Candidates should demonstrate actual implementation experience, not simply LangChain wrappers.

RAG Architecture Assessment

Assess whether the candidate understands end-to-end RAG architecture, including:

• Ingestion pipelines

• Chunking strategies

• Embedding selection

• Vector databases

• Retrieval optimization

• Response generation

• Guardrails

**Chunking methods for reference:**

• Semantic Chunking

• Recursive Chunking

• Structural Chunking

Parameters for Agentic AI Evaluation

Assess the candidate's understanding of the following metrics:

• Recall@K

• Precision@K

• MRR

• NDCG

• Context Recall

• Context Precision

Pay: Up to ₹3,200,000.00 per year

Work Location: Hybrid remote in Hyderabad, Telangana