Vice President - Engineering
First seen by Alion on Sep 15, 2026.
Location: Bengaluru, India - Hybrid (3 days/week in office)
Reporting to: CEO
Experience: Preferably 10 - 15 years of enterprise software engineering experience. Candidates with fewer years may be considered if they demonstrate exceptional hands-on engineering and leadership expertise.
About the Role:
We are looking for a senior technology leader to drive the organisation's product, AI and platform technology strategy while leading engineering excellence across AI/ML, data, platform engineering, DevOps, infrastructure and quality engineering.
This is a mission-critical leadership role requiring someone who combines strong hands-on technical depth with strategic engineering leadership and has experience building and scaling enterprise-grade B2B SaaS products.
The ideal candidate should have successfully taken AI/ML or GenAI solutions from early-stage prototypes to scalable production platforms, particularly involving AI agents, multi-agent orchestration, intelligent automation, complex workflows and document intelligence.
Key Responsibilities:
Technology & Product Leadership:
- Define and execute the overall technology vision, architecture and long-term platform roadmap.
- Lead the architecture, design and delivery of highly scalable enterprise systems.
- Drive engineering excellence, development velocity, scalability, security and reliability.
- Partner with executive leadership on business strategy, customer requirements and product delivery.
Engineering & Platform Leadership:
- Lead engineering functions across product technology, platform engineering, AI/ML, DevOps, infrastructure and Quality Engineering.
- Architect and scale cloud-native platforms across Azure, AWS and GCP.
- Drive distributed systems and microservices architecture.
- Own production reliability, uptime, engineering efficiency and cloud cost optimisation.
- Build, mentor and scale high-performing full-stack and machine-learning engineering teams.
GenAI & AI Strategy:
- Build scalable, production-grade GenAI, ML and enterprise data capabilities.
- Own GenAI/LLM solution architecture.
- Architect solutions involving AI agents, autonomous workflows and multi-agent orchestration.
- Lead the development of intelligent automation, data extraction and decision-intelligence solutions.
- Provide hands-on architectural oversight for LLMs, applied AI and deep-learning products.
- Build sophisticated document intelligence and intelligent document automation platforms, including solutions comparable to patent parsing, legal workflow automation and structured decision systems.
What Success Looks Like:
- AI Transformation: Build enterprise-grade AI capabilities leveraging GenAI, LLMs, ML, AI agents and data engineering.
- Platform Scaling: Architect and scale the technology platform to support enterprise customers and global growth.
- Engineering Culture: Build a high-performance engineering organisation focused on ownership, innovation, execution and continuous learning.
Required Experience & Qualifications:
- Preferably 10 - 15 years of experience in enterprise software engineering, B2B SaaS or technology-first product companies.
- Strong experience in engineering leadership and technology strategy.
- Proven experience taking AI/ML or GenAI prototypes into production-grade enterprise SaaS platforms.
- Hands-on experience with LLMs, AI agents, multi-agent systems and workflow orchestration.
- Experience with document intelligence, unstructured data processing or intelligent automation is highly desirable.
- Experience building and mentoring teams of full-stack, platform and ML/AI engineers.
- Proven experience defining and executing technology strategy, architecture and platform roadmaps.
- Strong cloud-native engineering expertise across Azure, AWS and/or GCP.
- Experience managing product delivery end-to-end, including production operations and customer support.
Technical Skills:
- Programming: Java, Python
- Frontend/Backend: JavaScript, React, Angular, Node.js
- AI: GenAI, LLMs, AI Agents, Applied AI, Deep Learning
- AI Architecture: Multi-Agent Orchestration, Autonomous Workflows, Decision Intelligence
- Data: SQL, NoSQL, Data Modelling, Unstructured Data
- Architecture: Distributed Systems, Microservices, Platform Architecture
- Cloud: Azure, AWS, GCP
- Engineering: DevOps, CI/CD, Git, Quality Engineering
- Methodologies: Agile
- Tools: Atlassian ecosystem
Leadership Competencies:
- Strong engineering and technology leadership.
- Ability to remain technically hands-on while leading at a strategic level.
- Strong product and delivery management capabilities.
- Experience working directly with senior executives and enterprise customers.
- Excellent stakeholder communication and influencing skills.
- Strong business acumen combined with deep technical expertise.
- Strong analytical, problem-solving and decision-making capabilities.
Key Skills:
- Engineering Leadership - GenAI / LLMs - AI Agents - Platform Architecture - Document Intelligence - Multi-Agent Orchestration - Distributed Systems - Microservices - Java - Python - React - Node.js - Azure - AWS - GCP - DevOps - Quality Engineering - Technology Strategy - B2B SaaS
Skills
CTO, Technical Strategy, IT Product Development, AI Product Development