Role Overview :

InfoBeans is looking for an experienced Technical Project Manager with a strong engineering background, AI/ML expertise, and proven leadership capabilities to manage and lead a 40+ member engineering team supporting BFSI.

The ideal candidate will combine technical depth, project and delivery management, client engagement, and a Forward Deployed Engineer (FDE) mindset. Beyond managing delivery against defined requirements, the candidate will work closely with client stakeholders to understand business challenges, identify opportunities for innovation, and rapidly translate ideas into working technical solutions using AI, automation, and modern engineering practices.

The role requires hands-on familiarity with Python, Django, Databticks, Spec-Driven Development (SDD), and agentic AI development. The candidate should be capable of engaging with business and technology stakeholders, guiding engineering teams through solution discovery and prototyping, and converting successful POCs into scalable, production-ready solutions.

Key Responsibilities :

1. Technical Project & Delivery Management :

- Lead and manage a 50+ member engineering team, ensuring predictable delivery, quality, productivity, and client satisfaction.

- Own end-to-end delivery governance, including planning, estimation, resource allocation, risk management, dependencies, budgets, and delivery metrics.

- Establish effective engineering processes, delivery standards, performance monitoring, and continuous improvement practices.

- Work closely with engineering leads, architects, business analysts, and client stakeholders to resolve technical and delivery challenges.

- Build a strong ownership culture focused on outcomes, accountability, collaboration, and continuous learning.

2. Forward Deployed Engineering & Client Partnership :

- Engage directly with client business and technology stakeholders to understand business objectives, operational challenges, and emerging requirements.

- Proactively identify opportunities where AI, automation, data engineering, and modern software engineering can deliver measurable business value.

- Facilitate discovery workshops, technical discussions, and solution-design sessions to translate business problems into actionable engineering solutions.

- Rapidly develop prototypes and POCs to validate ideas, demonstrate feasibility, and accelerate client decision-making.

- Bridge the gap between business needs and engineering execution, helping transform exploratory opportunities into funded projects and higher-value engineering engagements.

- Build trusted client relationships by demonstrating technical credibility, business understanding, and a solution-oriented approach.

3. AI/ML, Agentic AI & Modern Engineering :

- Drive the identification, design, and development of AI/ML-based POCs addressing real-world business and technology challenges.

- Demonstrate practical knowledge of Python and Django, including the ability to review code, guide implementation, and troubleshoot technical issues.

- Lead or guide the development of AI-powered applications, LLM-based solutions, AI agents, and agentic workflows.

- Apply Spec-Driven Development (SDD) and AI-assisted engineering practices to improve development speed, consistency, quality, and maintainability.

- Encourage the use of coding assistants, AI agents, automated testing, and modern developer productivity tools across engineering teams.

- Evaluate POCs for technical feasibility, security, scalability, performance, and readiness for production deployment.

- Establish reusable patterns, reference architectures, and engineering practices that support repeatable AI-led solution delivery.

4. Technical Leadership & Engineering Excellence :

- Provide technical direction to engineering teams and ensure alignment with enterprise architecture, coding standards, security requirements, and engineering best practices.

- Work with architects and senior engineers on solution design, technical decision-making, integration, and non-functional requirements.

- Promote hands-on problem-solving and maintain sufficient technical depth to challenge assumptions, review proposed solutions, and guide teams effectively.

- Drive collaboration across application engineering, data engineering, QA automation, DevOps, and AI/ML teams.

- Ensure that AI-enabled solutions meet applicable financial-services security, privacy, governance, and compliance requirements.

5. Stakeholder Management & Business Growth :

- Communicate effectively with senior client stakeholders, internal leadership, and cross-functional teams.

- Present technical proposals, POC demonstrations, solution roadmaps, delivery updates, and business-value outcomes.

- Identify opportunities to expand existing engagements through innovation, solution-led discussions, and measurable business outcomes.

- Collaborate with account leadership and business development teams to shape proposals, estimates, solution approaches, and new engineering opportunities.

- Track and communicate business impact through metrics such as productivity improvement, cycle-time reduction, quality, cost optimization, and value delivered.

Required Skills & Experience :

- Experience : 15+ years in the IT industry, with substantial experience in technical project management, engineering leadership, and enterprise application delivery.

- Team Leadership : Proven experience managing large engineering teams, preferably 40 - 50+ members, in complex client environments.

- Programming : Strong hands-on experience with Python and practical exposure to Django or related Python web frameworks.

- AI/ML : Demonstrated experience building AI/ML proof of concepts, with the ability to translate business problems into working technical prototypes.

- Generative AI & Agentic Development : Practical exposure to LLM-based applications, AI agents, agentic workflows, and AI-assisted software development.

- Spec-Driven Development : Understanding and practical experience with SDD, including translating requirements into specifications, implementation plans, and testable engineering outcomes.

- FDE Mindset : Experience engaging directly with clients, conducting discovery, solving ambiguous problems, prototyping solutions, and driving ideas toward implementation.

- Technical Architecture : Good understanding of application architecture, APIs, integrations, databases, cloud platforms, CI/CD, testing, and production-readiness practices.

- Delivery Management : Strong capabilities in project planning, estimation, risk management, governance, stakeholder alignment, and delivery execution.

- Communication : Excellent verbal, written, presentation, negotiation, and stakeholder-management skills.

Preferred Qualifications :

- Experience in banking, financial services, or other regulated enterprise environments.

- Familiarity with banking technology, risk management, financial operations, or enterprise transformation initiatives.

- Experience working with global clients and distributed onsite/offshore engineering teams.

- Exposure to cloud platforms, data engineering, RAG-based applications, AI evaluation, observability, and secure enterprise AI adoption.

- Experience converting innovation initiatives and POCs into production solutions or larger engineering engagements.

- Relevant technical, cloud, AI/ML, or project-management certifications are an advantage.

Key Success Measures :

- Successful leadership and delivery of the 50+ member engineering team.

- Improved delivery predictability, engineering productivity, quality, and client satisfaction.

- Identification and validation of high-value business problems through client discovery.

- Successful development and demonstration of AI/ML POCs and agentic solutions.

- Adoption of SDD and AI-assisted engineering practices across relevant teams.

- Conversion of validated POCs into production implementations and incremental engineering opportunities.

- Strong client relationships and recognition as a trusted technical and business partner.

Ideal Candidate Profile :

We are looking for a technology leader who is not limited to managing plans, schedules, and status reports. The ideal candidate is a technically credible engineering leader who can engage with clients, understand their business problems, build or guide rapid prototypes, lead large teams, and turn AI-driven innovation into tangible business outcomes.