Technical Project Manager- AI/ML

Role overview

Technical Project Manager- AI/ML at Relanto

Lead end-to-end delivery of software development, AI/ML, Data Engineering, and Analytics projects .

Role Summary We are looking for an experienced Technical Project Manager to lead application development, AI/ML, Data Engineering, and Analytics initiatives.

The role requires the ability to manage projects end-to-end, work effectively with technical and cross-functional teams, manage stakeholders and budgets, and ensure projects are delivered on time, within scope, and within budget.

Responsibilities

• Develop and maintain project plans, roadmaps, milestones, timelines, budgets, resource plans, and delivery schedules.
• Manage multiple projects and ensure alignment with business and portfolio priorities.
• Collaborate with developers, architects, data engineers, data scientists, ML engineers, QA teams, product managers, and business stakeholders .
• Translate business requirements and technical concepts into clear project plans, deliverables, milestones, and success criteria.
• Manage project scope, schedule, budget, resources, risks, issues, dependencies, and change requests.
• Proactively identify and resolve delivery challenges and technical dependencies.
• Drive clear ownership and accountability across project teams and ensure timely execution.
• Facilitate Agile/Scrum ceremonies and promote effective Agile delivery practices.
• Work closely with technical leads and architects to understand solution architecture, integrations, data flows, technical risks, and dependencies .
• Demonstrate working knowledge of AI/ML workflows, data pipelines, model development, model deployment, and MLOps concepts .
• Monitor project progress using tools such as JIRA, Confluence, Azure DevOps, MS Project, or equivalent .
• Prepare and present project status reports, dashboards, risks, financials, and milestone updates to leadership and clients.
• Manage stakeholder and client expectations and ensure clear communication of commitments, timelines, risks, and decisions.
• Collaborate with internal teams to ensure successful integration and alignment with organizational objectives.
• Support pre-sales activities, proposal development, estimation, project scoping, and client discussions for technology and AI/ML initiatives.
• Drive continuous improvement in project delivery processes, quality, and team collaboration.
• Stay updated on emerging AI/ML, data, cloud, and software engineering technologies relevant to project delivery.
• Required Qualifications & Experience Bachelor's or Master's degree in Computer Science, Engineering, Technology, or a related field . 8+ years of experience in technology/software development environments , with strong project management experience.
• Proven experience managing end-to-end software/application development projects .
• Experience managing or delivering AI/ML, Data Engineering, Analytics, or data-driven projects .
• Strong understanding of SDLC, Agile/Scrum methodologies, and software development processes .
• Working knowledge of: Software architecture and application development APIs and system integrations Data pipelines and data engineering AI/ML development and deployment lifecycle Cloud and modern technology platforms Experience managing budgets, resources, timelines, risks, dependencies, and project governance .
• Proven ability to deliver projects on time, within scope, and within budget .
• Strong stakeholder, client management, communication, leadership, and presentation skills.
• Ability to translate technical information into clear business and project decisions.
• Strong problem-solving and decision-making abilities.
• Ability to establish accountability and provide clear direction to project teams.

Employment details

• Location: Bengaluru [KA] [India]

Additional role details

• The ideal candidate will combine strong project management capabilities with a solid understanding of software development and modern technology environments.
• The Technical Project Manager should be technically conversant enough to understand software architecture, SDLC, data pipelines, AI/ML workflows, integrations, and technical dependencies, while maintaining a strong focus on business outcomes and delivery.