Azalio
Technical Delivery Lead – AI Solutions
Gurgaon·Full Time·On-site·4-6 years
Project managementAI solution architecturestakeholder managementAgile methodologiesteam leadershiprisk managementcloud computingdata analyticsmachine learning lifecyclecommunication skillsproblem-solvingbudgetingvendor managementsoftware development lifecyclechange management
Role Overview
Technical Delivery Lead – AI Solutions
Experience: 5–8 Years
Location: Gurgaon / NCR
Employment: Full-time
Domain: AI | GenAI | Agentic AI | Telecom | Enterprise Solutions
About the Role
- Azalio Technologies is expanding its AI practice across Telecom and Enterprise customers and is looking for a Technical Delivery Lead – AI Solutions to own customer-facing AI initiatives from requirement discovery through implementation, demonstration and acceptance.
- This is not a coordination-only project management role. We need someone who can work across customers, engineering teams, architects and leadership, convert ambiguous requirements into an executable plan, drive dependencies, remove blockers and ensure committed outcomes are delivered.
- The candidate should be technically strong enough to participate meaningfully in AI architecture and engineering discussions while bringing strong execution and stakeholder-management skills.
What We Are Looking For
- 5–8 years of experience in technical delivery, solution delivery, technical program management or product/solution engineering.
- Strong experience leading cross-functional technical teams.
- Experience working directly with enterprise customers and technical stakeholders.
- Ability to independently manage requirement workshops, technical discussions, demos and escalations.
- Strong understanding of software development and solution delivery lifecycle.
- Ability to break ambiguous problems into clear execution plans.
- Strong ownership, problem-solving and communication skills.
- Comfortable working in fast-moving environments where requirements evolve during execution.
Technical Exposure
Working knowledge of several of the following:
GenAI / LLMs
AI Agents / Agentic AI
APIs and system integration
Git / GitHub / GitLab
CI/CD
Databases and data platforms
Kubernetes / OpenShift
REST / JSON / YAML
Logs, observability and application environments
The candidate does not need to be the deepest AI developer, but must understand the technology sufficiently to challenge engineering assumptions and drive technical delivery.
Telecom Experience
Telecom experience is preferred, particularly in:
- OSS/BSS, Network Automation, Cisco NSO, Service Provisioning, Network Assurance, Autonomous Networks, Telco Cloud, Inventory or Orchestration.
- Strong AI technical-delivery candidates from other enterprise domains will also be considered.
Ideal Profile
We are looking for someone who is:
High ownership | Execution-driven | Structured | Proactive | Technically curious | Customer-focused | Persuasive | Decisive | Comfortable with ambiguity
What Success Looks Like
You should be able to take:
We want to use Agentic AI to automate this process.”
and drive:
- Problem → Discovery → Scope → Architecture → Execution → Validation → Demo → Customer Acceptance
- Success means engineering teams know what to deliver, dependencies are closed early, customers see measurable progress, and PoCs reach successful acceptance.
Why Azalio
- Azalio is building its next phase of growth around AI, Automation and Autonomous Operations, alongside its Telecom, OSS, Cloud and Network Engineering capabilities.
- This role offers significant ownership in taking real customer AI initiatives from concept to working solution.
Location: Gurgaon / NCR
Experience: 5–8 Years
Joining: Immediate / early joiners preferred.
What You Will Do
- Own AI, GenAI and Agentic AI PoCs and solution deliveries end-to-end.
- Translate customer requirements into clear use cases, scope, milestones, workstreams and acceptance criteria.
- Lead cross-functional teams of AI engineers, developers, architects, SMEs and integration teams.
- Drive customer and internal dependencies including infrastructure, access, data, APIs, models, security approvals and SME inputs.
- Identify risks and blockers early and drive them to closure.
- Run customer workshops, technical reviews, progress meetings, demos and acceptance discussions.
- Maintain clear visibility of actions, owners, dependencies, decisions and timelines.
- Ensure different AI and application components come together as one working end-to-end solution.
- Convert customer feedback into actionable engineering priorities.
- Support transition of successful PoCs into scalable solutions and commercial offerings.
How We Work
Ownership-led delivery
We expect every team member to understand the problem, take responsibility and follow through.
Architecture-grounded engineering
Design is validated before implementation begins. Standards and governance are embedded throughout.
Evidence over assumption
Delivery is supported by documentation, runbooks, test results and acceptance evidence.
Continuous improvement
Lessons from every engagement are captured and reused across practices and programs.
Application Process
- 1Submit your application with CV and cover note below
- 2Our team will review your background and reach out within a reasonable timeframe
- 3Initial conversation to understand your experience and explore mutual fit
- 4Technical and role discussion with the practice team
- 5Offer and onboarding