VP of R&D

TRG is on a mission to make the world a safer place. We build intelligence and data-fusion solutions that help law-enforcement and intelligence agencies worldwide connect information across multiple domains and turn complex data into actionable insights.

Our technology brings together large volumes of fragmented data across different intelligence domains, helping investigators and analysts uncover connections, accelerate investigations and make better-informed decisions.

We operate with the ambition of a technology company that wants to lead the market, not simply follow it. Speed, experimentation, technical creativity and the ability to turn difficult ideas into real capabilities are fundamental to how we work.

The Role

We are looking for an experienced VP of R&D to lead and scale TRG’s engineering organization through its next stage of growth.

This is not a role focused only on managing delivery, processes or people. We are looking for a strong engineering leader who combines technical depth, product thinking, execution, innovation and people leadership.

You will lead our engineering organization across several technology domains, including Big Data and Data Fusion, AI, Geospatial Intelligence and OSINT. You will be directly involved in our Big Data, Data Fusion and AI engineering area while managing and developing the engineering leaders responsible for the other pillars.

A key part of the role is helping us scale without losing our startup mindset. We want stronger engineering foundations, leadership and accountability, without introducing unnecessary layers, processes or structures that slow down experimentation and delivery.

You will work closely with the CPO, CTO, Product, Engineering Leaders and Applied Research to turn ambitious ideas, research and prototypes into scalable products and continuously strengthen TRG’s technical and market advantage.

The role reports directly to the Chief Product Officer and leads TRG’s engineering managers and technical leadership team.

What You’ll Do

Lead and scale the R&D organization

• Lead the engineering organization across Big Data & Data Fusion, AI, Geospatial Intelligence, OSINT and other emerging technology areas.
• Be directly involved in the leadership and technical direction of our Big Data, Data Fusion and AI engineering area.
• Manage and develop the engineering leaders responsible for the other product and technology pillars.
• Build a strong engineering leadership layer that can operate with increasing independence and ownership.
• Coach engineering managers and technical leaders, helping them strengthen their technical leadership, product thinking, decision-making and ability to build high-performing teams.
• Create clear ownership, accountability and decision-making without unnecessary management layers.
• Scale the organization while protecting speed, autonomy and the ability to experiment.
• Build an engineering culture based on ownership, high standards, collaboration and continuous delivery of value.
• Identify capability gaps early and build the teams, leadership and technical skills needed for the company’s next stage of growth.

Define and challenge the technical direction

• Own the engineering and technology direction in close partnership with Product and technical leadership.
• Stay close to architecture and important technical decisions rather than operating only through management layers.
• Challenge unnecessary complexity, repeated refactoring, weak architectural decisions and technical choices that create long-term delays.
• Provide strong technical direction across complex systems involving large-scale data ingestion, data fusion, distributed processing, analytics, AI and geospatial intelligence.
• Ensure our architecture supports increasing data volumes, new intelligence sources, new products and the rapid introduction of new capabilities.
• Guide architectural decisions across backend, data, AI, infrastructure and platform engineering.
• Make pragmatic trade-offs between scalability, reliability, security, maintainability and speed.
• Know when production-grade engineering is required and when an MVP or experiment is the right approach to validate an idea.
• Identify technical risks early and ensure teams take ownership of solving them.

Strengthen execution

• Translate company and product strategy into clear engineering priorities, plans and outcomes.
• Build an engineering organization that continuously delivers meaningful product value rather than optimizing only for output or delivery metrics.
• Improve execution, quality and predictability where needed without turning engineering into a process-heavy organization.
• Remove unnecessary dependencies, processes and organizational barriers that slow teams down.
• Establish appropriate standards for reliability, observability, testing, release management, security and operational readiness.
• Help teams balance new capabilities with scalability, stability and technical-debt reduction.
• Create transparency around progress, risks, dependencies and engineering capacity while maintaining strong team ownership.
• Use AI and modern engineering tools aggressively to increase engineering productivity and shorten the path from idea to production.

Connect Product and Engineering

• Build a strong connection between engineering decisions, product strategy and real customer problems.
• Ensure engineers understand why we are building something, not only what they have been asked to implement.
• Work closely with Product to find the best solution rather than treating requirements as fixed instructions.
• Challenge Product when technology can unlock a better solution, and challenge Engineering when technical complexity is preventing product progress.
• Encourage engineering leaders and teams to think about customer value, competitive advantage and product outcomes.
• Help turn prototypes, research and experimental capabilities into scalable products.

Drive innovation and technical advantage

• Make innovation a core responsibility of the R&D organization, not a side activity.
• Push the organization beyond implementing capabilities that already exist in the market.
• Work closely with Product, Applied Research and engineering teams to identify opportunities where TRG can be first to market.
• Encourage exploration across areas such as AI, Big Data, Geospatial Intelligence, OSINT and emerging technologies relevant to our products.
• Create an environment where teams can quickly prototype, test and learn from ambitious ideas.
• Identify new technologies and technical approaches that can create meaningful competitive advantage.
• Ensure successful experiments can transition quickly from MVPs into reliable and scalable product capabilities.
• Protect experimentation and technical creativity as the organization grows.
• Maintain a culture where teams look first for how an idea can succeed, rather than starting from the reasons it may fail.

Partner across the business

• Work closely with Product, Operations, Customer Delivery, Intelligence Solutions and commercial teams.
• Ensure engineering remains connected to real customer, operational and market needs.
• Communicate technical direction, priorities, risks and trade-offs clearly to executive and non-technical stakeholders.
• Contribute to company-level strategy and planning as a senior member of the leadership team.
• Create strong collaboration between Engineering and the rest of the organization rather than allowing engineering to become an isolated function.

About You

• Significant experience leading and scaling a complex engineering organization of approximately 80–150+ engineers, including engineering managers and senior technical leaders.
• Previous experience as a Head of R&D/Engineering, VP Engineering, Engineering Director, Group Engineering Manager, or in a role with comparable scope.
• Demonstrated ability to scale an engineering organization without losing speed, ownership, technical depth and a startup mindset.
• Strong track record of developing engineering managers and technical leaders into strong, independent leaders.
• Strong software engineering and architecture background, with the ability to go deep into important technical discussions and challenge senior engineers when needed.
• Strong understanding of complex, data-intensive and distributed systems.
• Experience with areas such as Big Data, data fusion, data modelling, distributed systems, data pipelines, analytics, AI systems and large-scale data processing.
• Experience owning technical strategy and architecture decisions across multiple teams or product areas.
• Strong product mindset and the ability to connect technical decisions with customer, product and business outcomes.
• Strong track record of improving engineering execution, quality, accountability and delivery.
• Pragmatic decision-maker who understands the trade-off between building something perfectly and getting something valuable into the hands of users quickly.
• Strong bias toward action, experimentation and solving problems.
• Comfortable challenging existing decisions and changing direction when evidence shows there is a better approach.
• Strong understanding of how AI is changing software engineering and how engineering organizations can use it to significantly increase their capabilities and speed.
• Clear and direct communicator who can align engineers, product leaders and executives.
• Comfortable operating in a fast-moving, international environment where the organization, products and technology are continuously evolving.

Strong Advantages

• Experience building investigation, intelligence, analytics, cybersecurity, fraud-detection or decision-support platforms.
• Experience with geospatial intelligence, location intelligence, mapping, movement analysis or other geospatial data systems.
• Experience with data-fusion products combining structured and unstructured information from multiple sources.
• Strong understanding of AI/ML systems, LLM-based capabilities or AI-native product development.
• Experience moving prototypes or research projects into scalable production products.
• Experience building organizations where Product and Engineering work as one team rather than separate functions.
• Experience delivering software for law enforcement, intelligence, government, defence or other complex environments.
• Experience leading distributed engineering teams across multiple countries and time zones.

Why Join TRG?

• Lead and shape an engineering organization working across Big Data, AI, Data Fusion, Geospatial Intelligence and OSINT.
• Build the next stage of our engineering organization while preserving the speed and mindset of a startup.
• Work on difficult technical problems involving large-scale data, AI and multiple intelligence domains.
• Have the freedom to challenge existing approaches and introduce better ways of building products and technology.
• Work closely with Product and Applied Research to turn ambitious ideas into capabilities that can define new markets.
• Have direct influence on company strategy, product direction and the technical foundations of the company.
• Help build an organization whose ambition is not simply to compete with the market, but to create capabilities the market has not seen yet.

Originally posted on Himalayas