AI Engineer - Generative AI
First seen by Alion on Oct 30, 2026.
About the Role :
We are looking for a hands-on AI Engineer to design, develop and deploy next-generation Agentic AI and Generative AI solutions at Incedo. The role involves building production-grade LLM applications, RAG pipelines, AI agents and intelligent automation solutions.
What You'll Own :
1. Agentic AI & GenAI Engineering :
- Design, develop and deploy production-ready GenAI applications, RAG pipelines and agentic workflows.
- Build AI agents using multi-agent orchestration, tool calling, memory and enterprise integrations.
- Work with frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen or LlamaIndex.
- Implement MCP-based integrations and connect LLMs with enterprise systems, APIs and data sources.
- Develop and optimize retrieval strategies, embeddings, vector databases and contextual search.
- Evaluate foundation models and select appropriate models based on performance, accuracy, cost and latency.
2. AI Evaluation, Quality & Governance :
- Develop evaluation frameworks for LLM applications, including accuracy, relevance and hallucination assessments.
- Implement prompt engineering, prompt versioning and regression testing.
- Establish guardrails for responsible AI, PII protection and secure prompting.
- Monitor model performance, latency, token consumption and application reliability.
- Troubleshoot and optimize RAG pipelines and agentic workflows.
3. Platform Engineering & Delivery :
- Build and deploy AI solutions on cloud platforms such as Azure, AWS or GCP.
- Develop scalable APIs and microservices using Python and related frameworks.
- Containerize applications using Docker and deploy using Kubernetes.
- Integrate AI applications into CI/CD pipelines and production environments.
- Collaborate with product managers, architects and engineering teams to deliver AI capabilities.
4. Technical Collaboration :
- Drive technical implementation and contribute to architecture and design discussions.
- Conduct code reviews and follow engineering best practices.
- Mentor junior engineers and contribute to technical knowledge sharing.
- Identify opportunities to improve reusable AI components and engineering practices.
What You'll Bring :
- 4 - 8 years of experience in software engineering, AI/ML or related engineering domains.
- At least 2 - 4 years of hands-on experience building AI/ML or GenAI solutions.
- Strong programming skills in Python and experience developing production-grade applications.
- Hands-on experience building LLM-based applications and RAG solutions.
- Experience with agentic AI frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen or LlamaIndex.
- Strong understanding of embeddings, vector databases, semantic search and retrieval optimization.
- Experience with Azure OpenAI, Azure AI, AWS Bedrock or Google Vertex AI.
- Familiarity with Docker, Kubernetes, REST APIs and CI/CD pipelines.
- Understanding of LLM evaluation, observability, prompt engineering and AI safety practices.
- Strong problem-solving, debugging and communication skills.
Skills
Artificial Intelligence, Machine Learning, Python, Generative AI, LangChain, Agentic AI, LangGraph, Azure, AWS, Google Cloud Platform, RESTful API