Manager Consulting Delivery- Technical Program Manager- DevOps-Cloud Platform Engineering(12+Years)

Company Profile:
Founded in 1976 CGI is among the largest independent IT and business consulting services firms in the world. With 94000 consultants and professionals across the globe CGI delivers an end-to-end portfolio of capabilities from strategic IT and business consulting to systems integration managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at .

Position: Manager Consulting Delivery- Technical Program Manager- DevOps-Cloud Platform Engineering
Experience: 12Years
Category: Software Development/ Engineering
Shift: General Shift (Flexibility required for global stakeholder engagements)
Location: Bangalore/Hyderabad/Pune/Mumbai
Position ID: J1026-0343
Employment Type: Full Time

Education Qualification: Bachelors degree in computer science or related field or higher with minimum 12 years of relevant experience.

Technical Program Manager accountable for delivering the CCOE transformation program: an Operations Control Plane and SaaS operating model for CGI Advantage serving 50 State & Local Government clients. The role is AI-first by mandate: the TPM is expected to design prove and scale AI-assisted operations across the program. It combines hands-on technical credibility someone who still builds prototypes and reviews code with large-scale program leadership across engineering operations and executive stakeholders and a demonstrated bias for speed and measurable outcomes.

Plan and run PI cadences: scope dependencies capacity exit criteria and transparent re-planning across all CCOE workstreams.
Drive wave-based rollouts (e.g. observability across multi-tenant AKS estates) within client change windows and government compliance constraints.
Build funding and business cases spanning multiple internal organizations; force decisions through steering with stated cost of delay.
Referee build-vs-buy and competing-architecture decisions against written criteria; time-box debates and document decisions with revisit conditions.
Lead vendor evaluation and enterprise contract negotiation for platform tooling pricing support SLAs security and compliance terms.
Report program outcomes without spin: MTTR escalation rate automation coverage and SLA adherence.
Partner with operations leadership on workforce transition: reskilling redeployment and adoption of new tooling and workflows including AI literacy and safe governed use of AI tooling.
Own the AI roadmap for operations: LLM-assisted triage RAG over runbooks tickets and telemetry agentic remediation and AI-assisted engineering workflows from prototype through production with evaluation guardrails and cost controls.
Define AI governance with security and compliance: data residency PII handling prompt and output logging human-in-the-loop gates and model/version change control for government clients.
Drive urgency through time-boxed delivery: bias to 24 week proof points kill or scale decisions on evidence and visible burn-down of the riskiest unknowns first.

Must to Have Skills:
Azure platform depth (primary cloud): AKS at multi-tenant production scale Azure networking (VNet Private Link Front Door App Gateway) Entra ID Azure Policy and landing-zone/Well-Architected design autoscaling tenancy isolation and cost management (FinOps reservations tagging chargeback).
Azure services breadth: Azure Monitor and Log Analytics (KQL) Managed Grafana Key Vault Storage API Management Functions and Container Apps Service Bus/Event Hubs Azure SQL and DevOps/GitHub integration. Observability: Understanding of OpenTelemetry-based stacks (traces logs metrics) sampling and retention economics and alert tuning at scale.
CI/CD and GitOps: Understanding of GitHub Actions Argo CD incremental builds and policy-as-code gates (OPA Kyverno Conftest) with container signing and scanning.
Infrastructure-as-code and configuration management: Terraform/OpenTofu Ansible and configuration-in Git with drift detection.
Identity and security: Understanding of SSO RBAC and JIT access patterns (Entra ID Keycloak); secrets and certificate lifecycle automation (Key Vault cert-manager ACME).
AI and GenAI fundamentals: LLM capabilities and limits prompt engineering context engineering structured output and function/tool calling fine-tuning vs. prompting trade-offs token and inference cost management and latency/quality trade-offs.
RAG and knowledge systems: chunking and embedding strategies vector and hybrid search (Azure AI Search pgvector or equivalent) re-ranking grounding and citation retrieval evaluation and mitigation of hallucination and data leakage.
Agentic and AI-assisted operations: multi-step agents and orchestration frameworks (LangChain/LangGraph Semantic Kernel or equivalent) Model Context Protocol (MCP) style tool integration and evaluation and observability of AI systems (eval harnesses golden datasets tracing drift monitoring).
Understanding of Azure AI stack: Azure OpenAI / Azure AI Foundry Azure AI Search model deployment and quota management private networking for AI endpoints content safety and responsible-AI controls.
Hands-on engineering ability: comfortable in Python (and/or Go or TypeScript) Git-based workflows SQL/KQL and shipping working prototypes without waiting for a team to be assigned.
Program tooling fluency: PI and agile planning at scale RICE or equivalent prioritization and dependency and risk management.


Good-to-Have Skills:
12 years in technology including 5 years running multi-team technical programs (815 initiatives) as a TechPM program lead or platform delivery lead.
Operations transformation: moving support and operations organizations from reactive firefighting to problem management and SRE practices.
FOSS-biased platform strategy with explicit commercial buy triggers; hands-on vendor MSA negotiation.
Developer platform delivery (e.g. Backstage) and production delivery of AI-assisted operations LLM assisted triage RAG-backed knowledge and runbook assistants and self-healing workflows with measured deflection.
Azure certifications or equivalent demonstrated depth (e.g. AZ-305 Solutions Architect AZ-400 DevOps Engineer AI-102 Azure AI Engineer).
Active hands-on builder personal projects open-source contributions or side builds using AI tooling; genuinely passionate about development and fast iteration.
Presenting to executive leadership: funding asks program reviews and candid at-risk status narratives.

• Containerization
• DevOps Engineering
• DevOps Engineering
• Docker
• Github Actions
• Kubernetes
• Ansible
• DevOps Specialist
• English
• Machine Learning
• Python
• Shell Script

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Life at CGI is rooted in ownership teamwork respect and belonging. Here youll reach your full potential because

You are invited to be an owner from day 1 as we work together to bring our Dream to life. Thats why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our companys strategy and direction.

Your work creates value. Youll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas embrace new opportunities and benefit from expansive industry and technology expertise.

Youll shape your career by joining a company built to grow and last. Youll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.

That same commitment to fairness extends to how we use technology. To support our recruitment team AI tools may be used to help assess applications though they never replace human judgement. All hiring decisions remain entirely in the hands of our recruitment professionals.

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