AI Project manager

Bachelor’s degree in Engineering, Computer Science, or a related discipline

• 8+ years of experience in project or programme management

• 3+ years of experience delivering AI, Machine Learning, Data, or Analytics programmes

• PMP, Agile, Scrum, or equivalent certification preferred

Education: B.E. Computer Science/IT degree (or any other engineering discipline)

Experience: 9+ years

 Work timings: 2:00 TO 11:00PM/ 6:30PM to 3:30 AM

Position Requirements:

• Program Strategy & Planning
• Own program charters, end-to end roadmaps, success criteria and alignment to business objectives.
• Translate company strategy into clear program priorities, milestones, and resource plans across multiple teams.
• Lead quarterly and long-range capacity planning, balancing scope, resources and timelines across workstreams.

•          Program Execution & Delivery

• Drive delivery of large, technically complex programs comprising multiple projects and teams; ensure on-time, high-quality outcomes.
• Orchestrate cross-functional dependencies, manage sequencing, and remove organizational impediments.
• Operate program-level release, milestone and launch processes; maintain program schedules and integrated plans.

•          Technical Leadership & Influence

• Maintain technical fluency across systems (APIs, services, data, infra, web and mobile platforms) to identify risks, trade-offs, and integration concerns.
• Partner with engineering leads and architects to surface technical dependencies, propose solutions, and influence technical direction.
• Lead technical intake, prioritization and change control for program scope.

•          AI Programs & Governance

• AI-specific program accountability: Own model lifecycle programs (experimentation → validation → deployment → monitoring → scale), model risk management, and coordination with MLOps and data science teams.
• Governance and control: Implement and maintain governance for clinical, editorial, regulatory, and AI-specific risks (bias, explainability, monitoring), coordinating policies and controls with legal, compliance, and domain stakeholders.
• Offshore reality: Design and operate for distributed teams—ensure timezone overlap strategies, clear escalation mechanics, minimize decision latency, and define RACI for offshore/onshore handoffs.
• Experience in mentoring engineering teams to integrate AI assistants into their daily development workflows to increase velocity and code quality.

•          Stakeholder Management & Communication

• Serve as primary program owner for senior leadership and business partners; run steering committees and executive reviews.
• Produce concise executive-level reporting (status, risks, mitigation, outcomes) and tailor communications for diverse audiences.
• Build strong cross-functional relationships and drive alignment through regular touchpoints and stakeholder feedback loops.

 •          Risk, Budget & Vendor Management

• Develop and maintain program-level risk registers, contingency plans, and escalation protocols.
• Manage program budgets, track spend vs. plan, and coordinate with finance and procurement as needed.
• Own vendor/third-party integration and delivery where applicable.

•          Process, Tools & Automation

• Establish program governance, templates, and tooling conventions to improve visibility and efficiency.
• Identify automation and tooling opportunities (including AI-assisted tooling) to reduce manual work and improve program telemetry.
• Drive PMO maturity: scalable processes, reporting, and knowledge management across the organization.

•          Measure Impact

• Define and track program success metrics and business outcomes; iterate to maximize value delivery.
• Ensure learnings are captured and operationalized for future programs.

Role & Responsibilities:

• 10+ years of program or technical project management experience delivering large-scale technical programs in fast-paced, matrixed organizations.
• Proven track record driving multi-team, cross-functional technical initiatives from concept to measurable business outcomes.
• Strong technical literacy (experience with APIs, backend services, cloud infrastructure, data flows and integrations).
• Advanced proficiency with Agile at scale methodologies (e.g., SAFe, LeSS, or equivalent) and deep SDLC knowledge.
• Experience with capacity planning, roadmaps, dependency management, and cross-team prioritization.
• Expert-level proficiency in JIRA and Confluence; comfortable with program/portfolio tooling (Aha!, Productboard, Roadmunk, Airtable, Smartsheet, BI dashboards).
• Excellent stakeholder management and executive communication skills; proven ability to influence without direct authority.
• Strong analytical and problem-solving skills; data-driven mindset.
• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• Fluent English.

•          Preferred

• Certifications such as PMP, CSM, SAFe Program Consultant (SPC), or equivalent.
• Experience in digital publishing, web/content platforms, AI/ML products, healthcare information systems, or digital media.
• Experience managing program budgets and vendor/contract relationships.
• Familiarity with emerging project automation and Agentic AI tools for program management and decision support.
• Prior experience mentoring PMs and leading PMO or program-level process change initiatives.

Our mission at Matterway is to eliminate friction in digital processes.

Through real-time automation and decision augmentation, we help users work more efficiently, reduce errors, and achieve better outcomes.

We are looking for a hands-on, client-focused problem solver to join our delivery team. You will work closely with enterprise clients to understand their processes and turn business challenges into intuitive automation and AI solutions.

Working at the intersection of client partnership, process discovery, and solution design, you will create solutions that deliver measurable value. You will also contribute to the evolution of Matterway's automation offering and help shape how agentic AI is applied to the future of work.

As part of our international team across Europe and India, you'll thrive in a fast-paced, startup-like environment where priorities evolve quickly, building trusted client relationships and turning ideas into practical solutions.

Responsibilities

• Own end-to-end delivery of automation & AI solutions for enterprise clients. You are the single point of accountability for deliverables, timelines, budgets and overall project success.
• Analyse business pain points and design intuitive experiences and interfaces that your users will love.
• Create detailed wireframes, mockups, and user stories, and work closely with developers to bring your vision to life.
• Use analytics to measure success after go‑live and ensure your solutions deliver real business impact.
• Build lasting client relationships that drive expansion and referrals.

What we are looking for

• 5+ years in client-facing roles where you've managed complex projects.
• Strong skills in business analysis, UI/UX, and project management.
• An undeniable sense of ownership: you're driven by results, not just tasks.
• Excitement about working in a fast‑paced, startup‑like environment.
• Exceptional written and verbal English. Other languages, especially German, are a plus

# Hiring: Technical Project Manager (TPM)

*Location:* Bangalore  

*Experience:* 8–12 years in software delivery, including 4+ years as a Project Manager/Technical Project Manager  

*Qualification:* B.E./B.Tech/MCA  

*Travel:* Occasional client-site visits

### Job Description

We are looking for an experienced Technical Project Manager to manage end-to-end software delivery, lead Agile teams, coordinate with clients, and oversee production releases.

### Key Responsibilities

•⁠ ⁠Manage project scope, timelines, budgets, resources, and deliverables.

•⁠ ⁠Lead Agile/Scrum ceremonies, sprint planning, and backlog management.

•⁠ ⁠Handle client communication, project reporting, risks, and escalations.

•⁠ ⁠Manage production releases, deployments, CI/CD, and rollback plans.

•⁠ ⁠Lead cross-functional teams of 10–30 members across Development, QA, DevOps, and UI.

•⁠ ⁠Ensure quality standards, UAT, and timely project delivery.

### Mandatory Skills

•⁠ ⁠Strong experience in Agile, Scrum, Kanban, and client project delivery.

•⁠ ⁠Technical background in Development or QA.

•⁠ ⁠Hands-on experience with Jira, Confluence, or Azure DevOps.

•⁠ ⁠Knowledge of CI/CD, Git, SDLC, APIs, databases, and AWS/Azure basics.

•⁠ ⁠Experience managing production releases and cross-functional teams.

•⁠ ⁠Excellent communication, leadership, and stakeholder management skills.

### Good to Have

PMP, CSM/PSM, SAFe, or ITIL certifications; experience in cloud, AI, or data projects.

*Interested candidates:* Apply with your updated resume highlighting relevant project management, technical, and team leadership experience.

Senior Product Manager – AI / B2B SaaS

Location: Bengaluru

Work Mode: Work from Office

Experience: 5+ years

Department: Product Management

About LeadSquared

LeadSquared is a leading Sales CRM for high-velocity revenue teams, helping businesses manage leads, sales processes, customer interactions, marketing, and revenue workflows at scale.

We serve businesses where large sales teams manage high volumes of leads and customer interactions, making speed, prioritisation, automation, and effective sales execution critical to revenue growth.

Role Overview

We are looking for a Senior Product Manager – AI to own the roadmap and end-to-end execution of AI products within LeadSquared.

Key Responsibilities

• Own the roadmap, prioritisation, and end-to-end execution for your AI product area.
• Understand customer problems and identify where AI can create meaningful, scalable value and translate them into clear product requirements and scalable solutions.
• Drive products from discovery and 0→1 development through launch, adoption, and iteration.
• Build and scale end-user-facing AI experiences that work reliably within enterprise workflows. 
• Make informed product decisions considering quality, latency, and scale trade-offs in production AI systems.
• Work closely with Engineering, Design, AI/ML, Data, and GTM teams to ship high-quality products.
• Define and track product adoption, engagement, customer outcomes, and business impact.
• Drive GTM, adoption, and continuous product optimisation.

What We're Looking For

• 5+ years of Product Management experience.
• 2+ years of hands-on Product Management experience building AI products.
• Strong B2B SaaS product experience.
• Experience in 0→1 product development and launches.
• Strong product discovery, prioritisation, roadmap management, and execution skills.
• Familiarity with AI evaluations (evals), observability, guardrails, and human oversight.
• Data-driven approach with strong understanding of product metrics.
• Excellent communication, problem-solving, and stakeholder management skills.
• Candidates from Tier 1 / Tier 1.5 / Tier 2 colleges preferred.

Good to Have

• Experience building products using GenAI, LLMs, RAG, AI Agents / Agentic AI, or ML-based decision systems.
• Experience in CRM, SalesTech, MarTech, or Enterprise SaaS.
• Experience building AI products for sales, revenue, operations, or other enterprise users.
• Experience taking an AI capability from an early prototype to a reliable, scalable enterprise product.
• Candidates who have built AI side projects will have a preference. Share links to live products, prototypes, demos, GitHub repositories, agents, or apps you’ve built.
•  

Director of Engineering (AI Solutions & Delivery)

About the Role

We are looking for a Director of Engineering to lead engineering execution and delivery across our enterprise AI solutions. This role combines strong engineering leadership with operational discipline, ensuring AI products move from technical design to production with predictable timelines, high quality, and reliable performance.

You will lead Engineering Managers and Tech Leads, oversee multiple engineering teams, and drive delivery excellence across AI-powered applications and platforms. The focus is on execution, technical quality, and organizational accountability, ensuring teams deliver scalable, production-ready AI systems without compromising reliability or engineering standards.

Key Responsibilities

1. Engineering Delivery & Execution

• Own engineering delivery schedules, translating product roadmaps into achievable sprint plans and release milestones.
• Establish measurable delivery targets, aiming for at least 85% on-time delivery across engineering teams.
• Identify and resolve cross-team dependencies, technical bottlenecks, and resource constraints before they affect delivery.
• Drive engineering process improvements across Agile development, CI/CD, automated testing, and release management.
• Monitor delivery metrics, sprint commitments, and release readiness to maintain predictable execution.

2. AI Quality, Evaluation & Governance

• Establish automated AI evaluation pipelines to measure hallucinations, relevance, groundedness, and contextual accuracy before production releases.
• Define quality benchmarks and evaluation criteria for LLM-powered applications and AI-driven workflows.
• Implement safety mechanisms, validation filters, circuit breakers, and human-in-the-loop fallbacks to manage unpredictable AI outputs.
• Oversee RAG pipelines, vector databases, data ingestion, and retrieval mechanisms to maintain accurate, reliable, and compliant context.
• Reduce production AI quality regressions through continuous evaluation, monitoring, and feedback loops.

3. Architecture, Scalability & Reliability

• Oversee the architecture of distributed systems and cloud-native applications to support scalability, availability, and performance.
• Drive reliability targets, including 99.9% uptime and low time-to-first-token (TTFT) latency for applicable AI applications.
• Partner with Staff and Principal Engineers to design resilient systems, including fallback mechanisms for model API failures, timeouts, and rate limits.
• Establish engineering standards for code reviews, observability, automated integration testing, and security compliance.
• Ensure production systems meet defined service-level objectives (SLOs) and performance benchmarks.

4. Engineering Leadership & Team Development

• Lead and develop Engineering Managers and Tech Leads, establishing clear ownership, accountability, and delivery expectations.
• Build a high-performance engineering culture focused on technical excellence, collaboration, and continuous improvement.
• Partner with Talent Acquisition to attract, assess, and hire strong software engineering and AI talent.
• Align engineering resources with business priorities, delivery commitments, and technical requirements.
• Address performance and execution challenges while maintaining team engagement and engineering quality.

Success Metrics: First 90 Days

First 30 Days

• Assess existing engineering workflows, delivery pipelines, and release processes.
• Establish baseline AI evaluation criteria and identify gaps in production quality.
• Take ownership of engineering delivery across teams and align expectations with Engineering Managers and Tech Leads.

First 60 Days

• Implement automated AI evaluation frameworks and establish measurable quality benchmarks.
• Improve cross-team coordination and resolve key delivery dependencies.
• Establish consistent sprint planning, release cadences, and delivery reporting.

First 90 Days

• Achieve at least 85% sprint commitment completion.
• Demonstrate measurable reductions in production AI quality regressions.
• Improve system reliability and stabilize latency against defined performance targets.
• Establish clear accountability and predictable delivery practices across engineering teams.

Qualifications & Requirements

• Experience: 14+ years in software engineering, including at least 5 years managing Engineering Managers or Tech Leads in enterprise or high-growth environments.
• AI/ML Expertise: Hands-on experience delivering AI-powered systems involving LLMs, RAG architectures, vector databases, prompt engineering, or model fine-tuning workflows.
• Engineering Delivery: Proven ability to lead multiple engineering teams and deliver complex technical initiatives from design through production launch.
• System Architecture: Experience with distributed systems, cloud-native backend infrastructure, and scalable APIs across AWS, GCP, or Azure.
• AI Quality & Reliability: Understanding of AI evaluation frameworks, production monitoring, hallucination mitigation, guardrails, and system reliability.
• Delivery Management: Strong experience with Agile methodologies, CI/CD, release planning, and engineering performance metrics.
• Leadership: Ability to establish accountability, manage competing priorities, and deliver against ambitious deadlines without compromising quality or team morale.

What Success Looks Like

The successful candidate will establish predictable engineering delivery, improve the quality and reliability of production AI systems, and build a culture of ownership across engineering teams. They will combine technical judgment with execution-focused leadership to ensure AI solutions are delivered on schedule, operate reliably, and meet enterprise expectations.

If you are passionate about building high-performing engineering teams and delivering enterprise-grade AI solutions at scale, we would like to hear from you.

Roles & Responsibilities

Product Strategy & Discovery

• Identify customer, business, and market opportunities through stakeholder engagement, customer research, discovery workshops, and data analysis.
• Define product vision, roadmap, value proposition, success metrics, and prioritization aligned with business objectives.
• Translate business and customer needs into product requirements, user stories, PRDs, and acceptance criteria.
• Own and continuously prioritize the product backlog based on business value, feasibility, dependencies, risks, and strategic priorities.

AI & Digital Innovation

• Identify and evaluate opportunities to leverage Generative AI, automation, and emerging technologies across products and business processes.
• Define AI-focused use cases, business cases, success metrics, user journeys, and MVP/PoC strategies.
• Collaborate with AI/ML, data, architecture, and engineering teams to convert AI opportunities into scalable product solutions.
• Drive adoption of AI across the product lifecycle and SDLC, including discovery, requirements management, development, testing, analytics, documentation, and support.
• Contribute to enterprise-wide AI initiatives and help scale successful AI PoCs into production-ready solutions.

Presales, Consulting & Solutioning

• Lead or contribute to RFP responses, proposals, client discovery sessions, workshops, and solution presentations.
• Understand client challenges and translate them into digital transformation, modernization, and AI-driven product opportunities.
• Develop solution concepts, use cases, product capabilities, roadmaps, value propositions, and implementation strategies.
• Partner with engineering, UX, architecture, delivery, and commercial teams to define scope, estimates, assumptions, dependencies, risks, and solution feasibility.
• Support client engagements and identify opportunities for account growth through product enhancements, modernization initiatives, and AI adoption.

Product Delivery & Governance

• Partner with UX, engineering, QA, architecture, and delivery teams to ensure successful product execution and delivery.
• Facilitate sprint planning, backlog refinement, UAT/SIT activities, release planning, production validation, and defect prioritization.
• Monitor product KPIs, delivery metrics, adoption, business outcomes, risks, and dependencies.
• Drive stakeholder alignment and continuous improvement throughout the product lifecycle.
• Mentor and guide Product Managers and product team members to strengthen product thinking, decision-making, stakeholder management, and delivery excellence.

Customer & Business Outcomes

• Leverage customer feedback, product analytics, experimentation, and market insights to drive continuous product improvement.
• Lead adoption and successful rollout of new capabilities through effective stakeholder engagement, communication, and change management.
• Ensure products and solutions deliver measurable customer, business, and operational outcomes.

Core Competencies

• Product strategy, discovery, roadmap planning, prioritization, and backlog management.
• Generative AI, AI product thinking, AI use-case identification, and digital innovation.
• Presales, consulting, solutioning, RFP response management, and client engagement.
• Strong business acumen with the ability to connect technology initiatives to business outcomes.
• Excellent communication, presentation, facilitation, and stakeholder management skills.
• Strong understanding of Agile/Scrum methodologies and end-to-end product delivery.
• Ability to collaborate effectively with engineering, architecture, UX, QA, data, and AI/ML teams.
• Strong analytical, problem-solving, and decision-making capabilities.
• Ability to manage ambiguity, multiple workstreams, and senior client stakeholders.

Qualifications

• B.E./B.Tech in Computer Science, Information Technology, Engineering, or an equivalent discipline.
• MBA or certifications in Product Management, Business Analysis, or related fields preferred.
• 10+ years of experience in Product Management, Product Ownership, or Business Analysis.
• Experience working in Agile/Scrum environments with cross-functional technology teams.
• CSPO, PSPO, CBAP, or CCBA certifications are desirable.

Location - India (Remote)

Senior Technical Manager

Primary objective: Own engineering teams, architecture, delivery governance and successful execution of product and AI initiatives across DocTutorials.

Location

Hyderabad / Chennai

Employment

Full-time

Experience

10+ years

Role Summary

The Senior Technical Manager combines technical leadership, people management, product delivery and project execution. The role is accountable for team outcomes, engineering quality, timelines, production stability and the disciplined delivery of AI projects.

Key Responsibilities

1. Technology and Architecture Leadership

·       Provide direction for Python FastAPI, React/Next.js, data, cloud and AI architectures.

·       Review solution designs for security, scalability, maintainability, performance and cost.

·       Define engineering standards and resolve complex cross-team technical risks.

·       Remain technically hands-on through architecture reviews, critical code reviews and incident debugging.

2. People and Delivery Management

·       Lead, mentor and develop engineering teams with clear goals and accountability.

·       Own estimation, capacity, execution, dependencies, risks, releases and delivery recovery plans.

·       Conduct regular one-to-ones, performance reviews, coaching and skill-development planning.

·       Work with Product, QA, DevOps and stakeholders to deliver measurable product outcomes.

3. AI Project Execution

·       Assess AI use cases for feasibility, data readiness, risk, cost and measurable value.

·       Lead delivery of LLM, RAG, agentic and AI-assisted product initiatives from PoC to production.

·       Ensure evaluation, human validation, security, privacy, observability and rollback controls.

·       Prevent isolated demos, uncontrolled AI usage and dependency on individual engineers or vendors.

Required Skills and Experience

·       10+ years in software engineering with significant technical and people leadership experience.

·       Strong understanding of Python/FastAPI, React/Next.js, APIs, databases, cloud and distributed systems.

·       Proven ownership of product delivery, project planning, risk management and production operations.

·       Experience hiring, mentoring, evaluating and developing engineering teams.

·       Strong knowledge and execution experience across AI/ML, LLM, RAG or agentic-AI projects.

·       Practical understanding of Generative AI, LLMs, RAG, Agentic AI and responsible AI use relevant to the role.

·       Ability to use approved AI tools productively while protecting source code, credentials, learner data and organisational information.

·       Commitment to human review, testing, security validation and traceability for AI-assisted outputs.

Good-to-Have Experience

·       EdTech or medical-learning product experience.

·       AWS, Kubernetes, DevSecOps, MLOps or LLMOps.

·       Experience scaling teams and platforms through major transformation.

How Success Will Be Measured

·       Delivery becomes predictable with risks identified early.

·       Engineering quality, security and production stability improve.

·       AI projects progress from validated use cases to reliable production outcomes.

·       Team capability, ownership, engagement and succession strength increase.

·       Work consistently delivers measurable outcomes and business value—not merely completion of assigned tasks or activities.

Expected mindset: Own the outcome, use AI responsibly, communicate risks early and deliver secure, measurable value for DocTutorials and its learners.

-Turn ambiguous ideas into clear product requirements and workflows.

- Break large ideas into small experiments that can be shipped quickly.

- Communicate customer problems, edge cases, and product intent clearly to engineers and designers.

- Work closely with engineering throughout implementation rather than simply handing over a PRD.

- Test the product yourself and continuously improve it based on actual usage.

### Customers & Market

- Speak directly with customers and prospects.

- Understand how they currently solve problems and where existing tools fail.

- Run product demos and gather structured feedback.

- Separate individual customer requests from broader product opportunities.

- Use customer conversations to continuously refine product strategy.

### Launch & Growth - Own launch strategy for the products and features you build.

- Define positioning, messaging, demos, onboarding, and initial adoption strategy.

- Work across product, engineering, sales, and customers to make launches successful.

- Measure what happened after launch and iterate quickly.

## What We're Looking For

-You likely have **2–4 years of experience** across product, engineering, startups, consulting, AI, or related roles. More importantly, you should have: - **~1 year of hands-on experience building with LLMs, agents, or AI applications.**

- Built actual AI workflows rather than only used ChatGPT or managed an AI project.

- Strong product judgment and ability to simplify complicated problems. - Comfort working with engineers and understanding technical trade-offs.

- Ability to perform deep market and customer research independently. - Strong written and verbal communication.

- High ownership — you naturally move from identifying a problem to getting something shipped.

- Comfort operating in an environment where the answer is often not known beforehand.

## Two Traits We Care About Deeply

### Constraint Thinking Great product people don't start with: *"What could we build?"* They start with: *"Given our users, technology, time, team, data, and constraints, what is the smartest thing we can build?"*

We value people who can reduce a large possibility space into a small number of high-leverage decisions. You should be able to distinguish between: -

interesting vs. useful,

- possible vs. reliable, AI Product Manager 2 / 4 AI Product Manager - demoable vs. production-ready,

- customer requests vs. underlying problems,

- AI capability vs. AI product.

### Grounded Energy AI moves incredibly fast, and it is easy to either become overly skeptical or overly excited. We want someone who has **high energy without hype**. You should be excited enough to constantly experiment with new technology, while grounded enough to recognize its limitations. You should naturally ask:

- Does this actually work?

- How often does it fail?

- What happens at scale?

- Can we evaluate it?

- Will customers actually change their behaviour for this?

- Is AI even necessary here?

## You Might Be a Great Fit If You have independently done things like: - Built an agent over a weekend to test a product idea.

- Compared multiple LLMs for a real use case.

- Created an eval dataset to test AI quality.

- Used tools such as Claude Code, Codex, Cursor, LangGraph, OpenAI Agents SDK, MCP, Langfuse, or similar systems.

- Automated parts of your own product or research workflow with agents.

- Interviewed users and changed the product based on what you learned.

- Gone from idea to prototype to customer feedback to production. - Read product documentation, GitHub repos, Reddit discussions, research papers, and competitor products to understand a market deeply.

## This Role Is Probably Not For You If

- You primarily see PM as backlog management and sprint coordination. - You need detailed requirements before you can start working.

- You prefer delegating prototyping and experimentation entirely to engineering.

- You haven't spent meaningful time building with modern AI tools.

- You enjoy creating large strategy documents more than testing ideas with users.

- You are uncomfortable making decisions with incomplete information.

## What Success Looks Like Within your first few months, you should be able to independently: AI Product Manager 3 / 4 AI Product Manager - understand a customer problem,

- research the market,

- identify a promising product opportunity,

- prototype an AI workflow,

- define how its quality should be evaluated,

- work with engineering to productionize it,

- speak with early users,

- launch it,

- measure adoption,

- and recommend what we should do next.

About Solutionara

Solutionara is a U.S.-based IT Consulting and Technology Services firm with a Global Delivery Center in Noida, India.

As a fast-scaling consulting firm, we operate with high ownership, lean teams, and disciplined execution. We are also evolving toward an AI-enabled delivery model, focused on enterprise integration, digital transformation, and scalable technology solutions for global clients.

Our GDC plays a critical role in building high-impact engineering and delivery teams while driving operational excellence through structured processes and intelligent automation.

Location: Noida, Uttar Pradesh | On-site

Experience: 5–9 Years

Employment: Full-Time

Industry: IT Consulting & Technology Services

About the Role

Solutionara is looking for a Technical Project Manager – Enterprise Technology to join our Global Delivery Center in Noida.

This is a hands-on technology delivery role for someone who can operate effectively between project management and engineering teams. You will be responsible for translating technical work into structured delivery plans, coordinating cross-functional engineering teams, managing technical dependencies and risks, and driving projects from planning through deployment and stabilization.

You will work closely with Solution Architects, Technical Leads, Developers, Integration Engineers, Data Engineers, DevOps, QA, Business Analysts, client stakeholders, and vendors.

This role requires more than maintaining Jira boards and scheduling meetings. We are looking for someone who understands how technology projects are actually delivered and can ask the right questions when architecture, environments, APIs, integrations, infrastructure, data, testing, or deployment dependencies begin affecting the plan.

What You'll Do

Technical Project Delivery

• Manage technology projects from requirements and planning through development, integration, testing, deployment, and hypercare.
• Build and maintain detailed project plans, milestones, technical workstreams, dependencies, deliverables, and release schedules.
• Translate technical activities and engineering estimates into executable delivery plans.
• Coordinate work across application development, integration, cloud/DevOps, data, QA, architecture, and infrastructure teams.
• Understand technical blockers sufficiently to identify their delivery impact and drive the appropriate teams toward resolution.
• Challenge assumptions, timelines, estimates, and dependencies when delivery risks emerge.
• Ensure technical decisions, dependencies, assumptions, and actions are documented and followed through.

Delivery Governance & Control

• Maintain RAID logs, dependency trackers, decision logs, action items, milestones, and project health indicators.
• Identify schedule, resource, technical, environmental, integration, and deployment risks before they become delivery failures.
• Establish clear ownership and due dates for risks, issues, dependencies, and actions.
• Track planned versus actual progress and develop recovery plans when projects begin to slip.
• Manage scope changes and coordinate impact assessments across schedule, resources, technical dependencies, and delivery commitments.
• Escalate issues with clear impact, options, recommendations, and required decisions.
• Maintain accurate project documentation and delivery visibility for leadership and stakeholders.

Engineering & Cross-Functional Coordination

• Work closely with Solution Architects and Technical Leads to understand solution architecture and implementation dependencies.
• Coordinate API, integration, application, infrastructure, data, security, environment, and testing dependencies.
• Facilitate technical planning and dependency discussions across engineering teams.
• Coordinate development readiness, QA readiness, UAT, release readiness, cutover, deployment, and production stabilization.
• Ensure environments, access, infrastructure, test data, interfaces, and external dependencies are available when required.
• Track defects, technical blockers, and production-readiness items through closure.
• Support technical teams without attempting to replace the engineering or architecture functions.

Client & Stakeholder Management

• Participate in and lead client status meetings, delivery reviews, technical coordination meetings, and project governance discussions.
• Communicate technical issues in clear business and delivery terms.
• Provide concise project health reporting covering progress, risks, dependencies, decisions, and upcoming milestones.
• Manage stakeholder expectations around scope, timelines, dependencies, and delivery risks.
• Coordinate across India and global teams working in distributed delivery environments.
• Maintain professional, transparent communication when projects encounter delays or technical challenges.

Agile, Release & Delivery Management

• Facilitate sprint planning, backlog readiness, delivery reviews, retrospectives, and other Agile ceremonies where applicable.
• Work with engineering leads to ensure stories and technical activities are sufficiently understood before execution.
• Track sprint commitments without treating Agile metrics as a substitute for actual delivery outcomes.
• Coordinate release planning, UAT, change readiness, cutover activities, go-live, and hypercare.
• Support Agile, Scrum, Waterfall, and hybrid delivery models based on project and client requirements.

AI-Assisted Project Delivery

• Use AI and automation tools to improve project planning, documentation, meeting outputs, risk identification, status reporting, and delivery visibility.
• Identify repetitive project-management activities that can be automated or streamlined.
• Encourage responsible use of AI within project workflows while maintaining appropriate review, confidentiality, and accountability.
• Help Solutionara evolve toward a more data-driven and AI-enabled technology delivery model.

What We're Looking For

• 5–9 years of overall experience in technology delivery, with meaningful experience as a Technical Project Manager, Project Manager, Technical Program Manager, Delivery Lead, or similar role.
• Experience managing software engineering, enterprise application, cloud, integration, data, infrastructure, or digital transformation projects.
• Strong understanding of the Software Development Life Cycle (SDLC) and how software moves from requirements through development, testing, release, and production.
• Sufficient technical fluency to communicate effectively with Architects, Developers, DevOps Engineers, Integration Engineers, QA, and other technical specialists.
• Hands-on experience with project planning, RAID management, dependency management, risk management, change control, and delivery reporting.
• Experience coordinating multiple technical workstreams and dependencies.
• Ability to identify when a technical issue affects the critical path and drive appropriate recovery actions.
• Strong client and stakeholder communication skills.
• Ability to bring structure, ownership, and accountability to ambiguous or fast-moving technology projects.
• Strong problem-solving and escalation-management skills.
• Comfortable working in a fast-paced consulting and Global Delivery Center environment.

Technical Fluency

The Technical Project Manager is not expected to be the Solution Architect or primary developer, but should be comfortable discussing and managing delivery around concepts such as:

• REST/SOAP APIs and enterprise integrations
• Application and microservices architecture
• Cloud infrastructure and AWS/Azure environments
• CI/CD and DevOps pipelines
• Databases and data dependencies
• Development, QA, UAT, staging, and production environments
• Authentication, access, networking, and security dependencies
• Deployment, cutover, rollback, and production support
• Defects, logs, monitoring, incidents, and root-cause analysis

The TPM should be able to understand what is blocked, why it matters, who owns it, what it affects, and what needs to happen next.

Preferred Experience

Experience in one or more of the following areas would be an advantage:

• Enterprise Integration – Dell Boomi, APIs, Middleware, EDI
• AWS or Azure Cloud
• DevOps and CI/CD
• Data Engineering or Data Platforms
• ERP, WMS, CRM, PIM/DAM, or enterprise applications
• Application or legacy modernization
• Microservices and API-led architectures
• Digital portals and enterprise applications
• U.S. or global client delivery
• Consulting or technology services organizations
• Onsite-offshore / Global Delivery Center delivery models

What Success Looks Like

• Projects have clear plans, ownership, milestones, and technical dependencies.
• Risks and blockers are identified early rather than discovered at the point of failure.
• Engineering teams have the information, access, environments, and decisions required to execute.
• Technical issues are translated into clear schedule and business impact.
• Delivery commitments are actively managed rather than simply reported.
• Clients and leadership receive accurate and timely visibility into project health.
• Releases and go-lives are planned, controlled, and supported through stabilization.
• Project-management overhead is reduced through effective use of automation and AI.
• Technical teams view the TPM as someone who helps delivery move forward, not simply someone who asks for status updates.

Why Join Solutionara?

• Manage meaningful enterprise technology and transformation initiatives.
• Work directly with experienced architects, engineering leaders, and global clients.
• Build exposure across Cloud, Integration, Data, DevOps, AI, and Digital Transformation.
• Develop toward broader Senior Project Manager, Program Manager, or Technology Delivery leadership responsibilities.
• Have real ownership of technology delivery rather than operating solely as a PMO coordinator.
• Help shape delivery practices as our Noida Global Delivery Center continues to scale.
• Work in an environment actively incorporating AI and automation into technology delivery.