Senior Software Engineer - GenAI Context Engineer

Position Description: At CGI, we’re a team of builders. We call our employees members because all who join CGI are building their own company - one that has grown to 72, professionals located in 40 countries. Founded in , CGI is a leading IT and business process services firm committed to helping clients succeed.

We have the global resources, expertise, stability and dedicated professionals needed to achieve. At CGI, we’re a team of builders. We call our employees members because all who join CGI are building their own company - one that has grown to 72, professionals located in 40 countries.

Founded in , CGI is a leading IT and business process services firm committed to helping clients succeed. We have the global resources, expertise, stability and dedicated professionals needed to achieve results for our clients - and for our members. Come grow with us.

Learn more at is a great opportunity to join a winning team. CGI offers a competitive compensation package with opportunities for growth and professional development. Benefits for full-time, permanent members start on the first day of employment and include a paid time-off program and profit participation and stock purchase plans.

We wish to thank all applicants for their interest and effort in applying for this position, however, only candidates selected for interviews will be contacted. No unsolicited agency referrals please. Job Title: Gen AI Position: SSE Experience: 6+ Years Category: Software Development/Engineering Job Location: Hyderabad Mode of Work: Hybrid (3 Days WFO) . 6+ years of experience in knowledge engineering, enterprise search, data engineering, AI engineering, or platform engineering roles. .

Experience building enterprise AI search or knowledge platforms in banking, financial services, healthcare, or other regulated industries. . Familiarity with knowledge graphs, ontology modeling, AI observability, and enterprise governance frameworks. . Understanding of responsible AI, groundedness evaluation, and enterprise compliance requirements for GenAI systems. .

Hands-on experience with Retrieval-Augmented Generation (RAG), semantic search, embeddings, vector databases, and enterprise knowledge systems. . Strong programming skills in Python and experience with API-based integrations. . Experience with GenAI and retrieval technologies such as: .

Azure OpenAI / OpenAI . Azure AI Search . LangChain / Semantic Kernel .

Elasticsearch / OpenSearch . Vector databases and embedding frameworks . Experience designing ingestion pipelines, metadata frameworks, chunking strategies, and contextual retrieval systems. .

Strong understanding of enterprise data governance, access control, lineage, and permission-aware retrieval. Experience integrating enterprise content systems including SharePoint, Confluence, Jira, document repositories, and enterprise APIs. . Familiarity with cloud platforms such as Azure, AWS, or GCP and containerized environments. .

Strong analytical, troubleshooting, and problem-solving skills. . Excellent communication and collaboration skills with the ability to work across engineering, architecture, governance, and business teams. Your future duties and responsibilities: Must to have: .

Design and implement enterprise Retrieval-Augmented Generation (RAG) architectures for GenAI platforms and applications. . Build and optimize semantic retrieval pipelines, vector search implementations, and contextual grounding frameworks. . Develop ingestion pipelines for enterprise knowledge sources including SharePoint, Confluence, Jira, APIs, databases, and document repositories. .

Define metadata, taxonomy, ontology, chunking, and embedding strategies to improve retrieval relevance and AI response quality. . Implement permission-aware retrieval and secure knowledge access aligned with enterprise governance and compliance requirements. . Design and optimize hybrid search architectures combining vector search, keyword search, and knowledge graph capabilities. .

Collaborate with Value Engineers, architects, and business stakeholders to translate enterprise knowledge into scalable AI-ready knowledge structures. . Improve groundedness, citation accuracy, retrieval precision, and hallucination reduction across GenAI solutions. . Maintain knowledge lineage, auditability, and contextual traceability for enterprise AI workflows.

Required qualifications to be successful in this role: Good to have: . Support AI evaluation, observability, and continuous improvement initiatives for retrieval quality and search performance. . Work closely with governance, security, and compliance teams to ensure responsible and secure enterprise AI knowledge access. .

Contribute to reusable enterprise knowledge engineering patterns and platform accelerators. Skills: CrewAI LangChain LangGraph LlamaIndex OpenAI Python