Developer Experience & Engineering Operations Lead

Job Description: EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect.

We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit www.exlservice.com .

Role Title: Developer Experience \& Engineering Operations Lead

BU/Segment: Digital

Location: Dublin, Republic of Ireland (Flexible hybrid working)

Employment Type: Permanent

Summary of the role:

EXL is expanding its Products, Platforms and AI engineering capabilities. We are looking for an experienced Developer Experience and Engineering Operations Lead to make it easier for engineering teams to deliver high\-quality software safely, consistently and at speed.

This role will define and improve the day\-to\-day developer experience across tooling, standards, workflows, automation, knowledge management, engineering operations and AI\-assisted delivery practices. The aim is simple: reduce friction, improve consistency, increase reuse and help teams deliver more value with less operational drag.

This is not a narrow tooling administration role. It is a cross\-functional leadership role that treats internal developers as customers and works across architecture, platform, product, delivery, security, cloud and engineering teams in Ireland, the UK, the US and India.

A significant part of the role will be to drive responsible adoption of AI across the software development lifecycle. You will help teams adopt AI coding assistants, engineering automation, prompt and context patterns, and EXL's AI platform capabilities, while ensuring adoption is measured by value delivered rather than tool usage alone. You will also act as an internal evangelist for EXLerate.ai and related platform capabilities, helping teams understand how to build, reuse, govern and operate AI\-enabled solutions effectively.

Some travel may be required for team, client or leadership meetings.

As part of your duties, you will be responsible for:

The role has five core areas of accountability:

• Developer Experience Strategy – Define the roadmap for improving how engineers build, test, release, operate and learn across EXL Engineering.


• Engineering Standardisation – Create pragmatic standards, reusable patterns, golden paths and playbooks that reduce duplication without slowing delivery.


• AI Adoption in Engineering – Drive the responsible use of AI\-assisted development, automation and agentic delivery practices across the software development lifecycle (SDLC).


• Engineering Operations Transformation – Improve operating cadences, knowledge sharing, decision\-making processes, tooling hygiene, onboarding and delivery transparency.


• EXLerate.ai Evangelism – Promote adoption of EXL platform capabilities for building, governing and operating reusable AI\-enabled solutions.

Key Responsibilities

• Define and execute the Developer Experience and Engineering Operations roadmap, aligned to EXL's Products, Platforms and AI engineering priorities.


• Identify the highest\-friction points in the engineering lifecycle through developer interviews, workflow analysis, metrics, delivery retrospectives and leadership input.


• Establish practical engineering standards, golden paths, reusable templates, delivery playbooks and reference workflows that help teams build and operate solutions consistently.


• Partner with Architecture, Platform Engineering, Cloud, DevOps, Security and Product Engineering teams to improve CI/CD, local development, build and test automation, environment management, release readiness, observability and operational feedback loops.


• Drive responsible AI adoption across the SDLC, including AI coding assistants, code review support, test generation, documentation automation, knowledge retrieval and agentic workflow opportunities.


• Create clear guidance for AI\-assisted engineering practices, including appropriate use, security boundaries, data handling, prompt and context patterns, review expectations and quality controls.


• Evangelise EXLerate.ai and related platform capabilities across engineering teams, helping teams understand where the platform should be used, how reusable assets should be created, and how AI\-enabled solutions should be governed and operated.


• Develop enablement programmes such as communities of practice, office hours, playbooks, internal demos, workshops, onboarding journeys and hands\-on adoption campaigns.


• Own the developer tooling adoption approach across IDEs, source control, CI/CD, documentation, internal portals, AI tools and engineering intelligence platforms, ensuring tools are useful, governed and adopted for measurable value.


• Define a measurement framework for Developer Experience, including adoption, satisfaction, friction reduction, cycle time, build and test reliability, onboarding time, tool effectiveness, quality signals and AI\-assisted engineering outcomes.


• Create structured feedback loops so engineering teams can contribute to standards, improve shared workflows and influence the roadmap for internal platforms and tools.


• Support engineering leaders in improving delivery transparency, operating cadences, decision management, documentation discipline and cross\-team dependency management.


• Ensure Developer Experience improvements are aligned with security, compliance, responsible AI, architecture governance and operational risk expectations.

Qualifications and experience we consider to be essential for the role:

• Significant experience in software engineering, platform engineering, developer experience, architecture, DevOps, SRE or engineering operations roles.


• Demonstrable track record improving developer productivity, engineering standards or delivery effectiveness across a multi\-team engineering organization.


• Strong understanding of modern software delivery practices, including cloud\-native development, APIs, microservices, CI/CD, test automation, secure SDLC, observability, operational readiness and release management.


• Experience defining standards, playbooks or golden paths that improve consistency while preserving team autonomy and delivery speed.


• Practical knowledge of modern engineering toolchains such as GitHub, GitLab or Bitbucket; CI/CD platforms; infrastructure as code; containers; developer portals; documentation platforms; IDEs; and AI\-assisted development tools.


• Experience evaluating, rolling out or governing AI tools, automation or productivity platforms within an engineering organisation.


• Ability to influence senior engineering, architecture, product, security and operations stakeholders without relying solely on formal authority.


• Strong written and verbal communication skills, with the ability to translate technical practices into clear guidance, adoption plans, executive updates and enablement materials.


• Data\-informed approach to decision\-making, with experience using metrics, qualitative feedback and adoption data to prioritise improvements.


• Experience working with globally distributed teams and creating practices that work across locations, time zones and delivery cultures.

Bachelor's degree in Computer Science, Engineering or a related discipline, or equivalent practical experience.

• Skills and Personal attributes we would like to have:


• Experience building or operating internal developer platforms, developer portals, platform\-as\-a\-product models or paved\-road engineering environments.


• Hands\-on experience with AI coding assistants, LLM\-powered engineering workflows, agentic development patterns, RAG, model gateways, prompt engineering, evaluations, guardrails or Responsible AI controls.


• Familiarity with engineering productivity and experience frameworks such as DORA, SPACE, DevEx surveys, value\-stream mapping or engineering intelligence platforms.


• Experience with AWS, Azure or GCP, including cloud\-native delivery patterns and cloud platform operating models.


• Experience improving onboarding, documentation, knowledge management or internal learning programmes for engineering teams.


• Experience in regulated industries such as insurance, banking, healthcare, utilities or other enterprise environments where security, governance and auditability matter.


• Public speaking, internal evangelism, training or thought leadership experience on developer productivity, AI adoption, platform engineering or software delivery transformation.

What success looks like:

• A clear Developer Experience roadmap is in place, grounded in developer feedback, measurable friction points and business priorities.


• Engineering teams have adopted a practical set of golden paths, standards, templates and playbooks for common delivery patterns.


• AI\-assisted development is being adopted responsibly, with clear guidance, enablement, governance and evidence of value beyond simple usage metrics.


• EXLerate.ai and related AI platform capabilities are better understood across engineering teams, with stronger reuse of common patterns, assets and platform services.


• Engineering operations are more consistent and transparent, with improved onboarding, documentation, delivery visibility, decision discipline and cross\-team collaboration.

Tooling, workflow and process duplication is reduced, and engineers can spend more time on product and platform outcomes rather than avoidable operational friction.

• **As part of a leading global Data and AI company, you can look forward to:

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