Technical Project Manager – AI & GenAI Delivery Job Description

AI Project Manager

About Techjays

At Techjays, we are driving the future of artificial intelligence with a bold mission to empower businesses worldwide by helping them build AI solutions that transform industries. As an established leader in the AI space, we combine deep expertise with a collaborative, agile approach to deliver impactful technology that drives meaningful change. Our global team consists of professionals from leading companies such as Google, Akamai, NetApp, ADP, and Cognizant.

Role Overview

We are seeking a seasoned Project Manager to oversee the successful delivery of complex AI-driven projects. You will be responsible for bridging organizational goals with cross-functional execution, ensuring that our technical teams deliver high-quality solutions on schedule and within budget.

Key Recruitment Details

• Experience Required: 8 + Years (Minimum 6+ years in end-to-end project management)
• Work Location: Coimbatore / Hybrid
• Target Joining Date: (ASAP / Within 30 days)

Must-Have Qualifications

• Proven Execution: 6+ years of experience managing the complete lifecycle of enterprise-grade software projects.
• Agile Expertise: Advanced proficiency in Agile/Scrum methodologies, with a track record of facilitating sprint planning, stand-ups, and retrospectives.
• Technical Proficiency: Mastery of project management tools including Jira, MS Project, or Trello.
• Strategic Planning: Demonstrated experience in resource allocation, risk mitigation, and contingency planning.
• AI Enthusiasm: Experience leveraging AI tools in project management or a demonstrated passion for adopting AI technologies to optimize workflows.
• Stakeholder Management: Exceptional communication skills for managing both internal cross-functional teams and external client relationships.

Roles & Responsibilities

• Project Governance: Plan, execute, and monitor projects to ensure alignment with client expectations and organizational benchmarks.
• Team Leadership: Facilitate high-performing Agile environments, fostering a culture of collaboration, innovation, and technical ownership.
• Risk & Budget Management: Identify potential bottlenecks early, implement mitigation strategies, and manage project budgets to ensure optimal resource utilization.
• Reporting & Transparency: Track project progress using modern metrics, preparing detailed reports and presentations for senior management.
• Continuous Improvement: Analyze project outcomes to implement best practices and drive operational discipline across the engineering organization.
• Mentorship: Elevate team members through active support and guidance, ensuring professional growth within the team.

Success Milestones

Timeline

Expectations

First 30 Days

Audit active project pipelines, establish stakeholder relationships, and assume management of ongoing sprint cycles.

First 60 Days

Optimize resource allocation workflows, streamline cross-team communication, and implement improved risk-tracking mechanisms.

First 90 Days

Achieve >85% sprint commitment completion rate and stabilize project delivery predictability across assigned teams.

What Techjays Offers

• Competitive Compensation: Best-in-class packages structured to reflect experience and impact.
• Health & Wellness: Medical insurance covering self and family up to ₹4 lakhs per person.
• Flexibility: A trust-based time-off policy and a flexible hybrid work model.
• Environment: A casual work culture with a diverse, multicultural team that respects ideas regardless of designation.
• Growth: Meaningful professional development in an innovation-driven culture.

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

Analytics Lead – AI & Decision Intelligence

Technical Leadership | People Management | Client Engagement | AI / Data / ML

About the Role

Our client is an enterprise AI and Decision Intelligence product company building advanced solutions for banking,

financial services and insurance. Its work spans predictive analytics, Machine Learning, Generative AI and Agentic AI,

with a strong focus on production-ready deployment, explainability, governance and measurable business outcomes.

The company is looking for an experienced Analytics Lead – AI & Decision Intelligence to lead a multidisciplinary team

of Data Scientists, ML Engineers, AI Engineers and other technical specialists.

This is a technical leadership, people management and client-facing role. The successful candidate is not expected to

be a hands-on expert in every area of AI, Data Science and Machine Learning. Instead, the ideal person will bring deep

expertise in at least one core AI/Data/ML discipline, together with the technical breadth and managerial capability to

lead specialists across multiple domains.

You will provide direction to technical teams, translate business problems into AI-led solutions, drive successful

delivery, and act as a key interface between highly technical teams and clients. A critical part of the role is the ability to

simplify complex technical concepts and communicate them clearly to senior and non-technical stakeholders.

What You’ll Do

 Lead and manage a multidisciplinary team of Data Scientists, ML Engineers, AI Engineers and Analytics

professionals.

 Provide technical direction across AI, Machine Learning and Data Science initiatives while enabling specialists to

own their areas of expertise.

 Translate business and customer requirements into appropriate analytical and AI solution approaches.

 Own delivery across scope, priorities, timelines, technical quality and business outcomes.

 Review and challenge technical approaches, solution designs and architecture without needing to be the hands-on

specialist in every area.

 Mentor, develop and motivate technical team members and build a strong culture of collaboration and

accountability.

 Establish and reinforce best practices around model development, deployment, governance, monitoring and

continuous improvement.

 Work closely with Product, Engineering, Sales and Customer Success teams on solution development and product

roadmaps.

 Lead client workshops, technical discussions and solution presentations.

 Explain complex AI and analytics concepts in simple, business-friendly language to senior and non-technical

stakeholders.

 Support pre-sales, solutioning and customer-facing technical engagements.

Technical Capabilities

Candidates should have strong exposure to the broader AI and Data Science ecosystem. Relevant capabilities include:

 Machine Learning & Deep Learning

 Statistical Modeling

 Python and SQL

 Data Science frameworks such as Scikit-learn, XGBoost, LightGBM, TensorFlow or PyTorch

 Data Engineering concepts and Feature Engineering

 Predictive and Prescriptive Analytics

 Model Explainability

 MLOps, CI/CD, model deployment and monitoring

 Generative AI and Large Language Models (LLMs)

 Retrieval-Augmented Generation (RAG)

 AI Agents and Agentic AI architectures

Analytics Lead – AI & Decision Intelligence | LinkedIn Job Description

 Prompt Engineering

 Responsible AI, model governance and regulatory considerations

 Cloud platforms such as AWS, Azure or Google Cloud

Important: You do not need to be an expert in all of the above. We are looking for deep expertise in at least one core

area of AI, Data Science, Machine Learning, ML Engineering, Generative AI, MLOps or Data Engineering, combined with

sufficient breadth to effectively lead experts in adjacent areas.

What We’re Looking For

 5–8 years of overall experience in AI, Data Science, Machine Learning, Analytics, Data Engineering or a related

technology discipline.

 Proven experience leading or managing teams of Data Scientists, ML Engineers, AI Engineers or similar technical

professionals.

 Strong people management, mentoring, delegation and team-building capabilities.

 Experience leading complex technical projects involving multiple specialist disciplines.

 Strong client-facing, stakeholder management and project delivery skills.

 Ability to communicate technical concepts clearly to non-technical audiences.

 Strong presentation skills and confidence engaging senior business stakeholders.

 Ability to balance technical considerations with business priorities and delivery objectives.

 Strong problem-solving, decision-making, organisational and managerial skills.

Preferred Experience

 Experience delivering AI or analytics solutions in Banking, Financial Services or Insurance.

 Exposure to use cases such as credit risk, fraud detection, customer acquisition, marketing analytics, collections,

deposits or pricing analytics.

 Experience working in an AI product, technology consulting or enterprise analytics environment.

 Exposure to Generative AI, LLM and Agentic AI programmes.

 Understanding of Responsible AI, explainability and regulatory considerations.

Education

 Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Statistics, Mathematics or a

related discipline.

 MBA preferred, but not essential.

The Profile We’re Looking For

We are looking for a technical leader who can lead experts — not someone expected to be the expert in everything.

Technical Depth + People Leadership + Client Management + Delivery Ownership

If you have strong expertise in one area of AI/Data/ML, have successfully managed technical teams, and can

confidently engage with both technologists and business leaders, 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)

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.

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.
•  

# 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 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.

Strong Senior Product Manager — Vertical Products (Fintech, Growth & Conversion) Profile

2

Mandatory(Experience 1)- Must have 6+ years of product management experience, with the most recent 3 years spent owning a consumer-facing product surface (app, web funnel, onboarding, checkout, or equivalent B2C surface).

3

Mandatory(Experience 2) - Must have consumer-facing product ownership as the centre of gravity. Backend, API, infra, or internal-tools PMs with no recent consumer-facing surface will not be considered. Backend exposure alongside real consumer-funnel work is fine; a backend centre not.

4

Mandatory(Experience 3)- Must have a metric-backed track record improving conversion, revenue yield, engagement, or lead quality in a consumer funnel — owned numbers, a steady experimentation cadence (A/B tests, rollouts, readouts), and comfort with analytics: funnels, cohorts, drivers, causal reasoning, measurement hygiene.

5

Mandatory(Experience 4)- Must be fluent with AI — active, habitual use of AI tools (ChatGPT, Claude, Gemini, Perplexity, or equivalent) in daily product practice.

6

Mandatory(Stakeholder Mgmt)- Must be able to act as the primary link between business leaders, tech teams, and external partners — communicating roadmap, priorities, trade-offs, and performance readouts to senior stakeholders, and working with distributed teams across time zones (Australia, India, Philippines).

7

Mandatory(Product Writing & Agile Delivery)- Must have strong product writing — problem briefs, PRD-lite/user stories, experiment plans, decision logs — and deep working command of Agile frameworks and tools.

8

Mandatory(Company) - Must be from B2C product company. FinTech is the priority . A non-fintech candidate qualifies only if currently or recently at a Series B plus company.

9

Preferred(Skill)- Exposure to LangChain, RAG, or prompt engineering in a product context; experience working directly with data science/ML teams on model-backed features; prior AI features in transactional or financial-services consumer UX.