AI Ops Engineer

Summary

Endava is a technology consultancy that combines engineering expertise, industry knowledge, and a people-centric approach to create digital platforms and experiences. The company is seeking an AI Automation Engineer – Level II to build an enterprise operational AI platform, developing LLM-powered agents, integrations, backend services, RAG pipelines, and progressively autonomous Infrastructure and Operations workflows.

Responsibilities

• Design, build, and enhance LLM-powered and agentic AI solutions for enterprise Infrastructure & Operations use cases
• Develop and integrate domain-specific AI agents that collaborate to answer questions, investigate operational issues, and execute defined workflows
• Build Model Context Protocol (MCP) integrations and tool-calling capabilities that securely connect AI agents with enterprise platforms and APIs
• Develop backend services and integrations primarily using Python and REST APIs
• Integrate the AI platform with infrastructure and operational systems such as ServiceNow/CMDB, Dynatrace, Zabbix, and GCP
• Build pipelines and services that ingest, normalize, enrich, and contextualize structured and unstructured operational data for AI consumption
• Implement Retrieval-Augmented Generation (RAG) and grounding strategies that provide LLMs with accurate enterprise context
• Develop initial read-only AI workflows supporting incident triage, incident management, root cause analysis (RCA), infrastructure discovery, and Help Desk automation
• Progressively extend workflows toward controlled automation, including change-window support, maintenance suppression, proactive outage prevention, and coordinated self-healing
• Apply appropriate guardrails, validation, access controls, and human-in-the-loop patterns as AI workflows move from recommendations toward autonomous actions
• Use modern AI-assisted engineering tools, such as Devin, Windsurf, or comparable platforms, to accelerate software development and automation
• Implement AI observability and evaluation capabilities to measure response quality, confidence, token consumption, reliability, latency, and operational outcomes such as MTTR
• Collaborate with AI architects, platform engineers, observability teams, IT operations, enterprise search, data, and security teams to deliver production-ready solutions
• Help improve knowledge quality and cross-validation mechanisms to reduce LLM hallucinations and ensure responses are grounded in authoritative enterprise data
• Contribute to engineering standards and reusable patterns for deploying secure, scalable, observable, and maintainable enterprise AI systems

Skills

• 3–5 years of overall relevant engineering experience, combining modern AI engineering with a strong software, integration, data, infrastructure, or AIOps foundation
• Approximately 1–2 years of hands-on experience with Generative AI/LLMs, including building applications or workflows using modern LLM platforms
• Approximately 2–3 years of foundational engineering experience in one or more areas such as backend software development, Python engineering, API integration, data engineering, cloud engineering, automation, or AIOps
• Strong programming skills in Python, including experience developing production-quality backend services and automation
• Strong experience designing, building, and consuming RESTful APIs and integrating multiple enterprise systems
• Practical knowledge of LLMs, prompt engineering, context management, embeddings, vector retrieval, and Retrieval-Augmented Generation (RAG)
• Hands-on experience with agentic or multi-agent AI frameworks, such as LangChain/LangGraph, AutoGen, CrewAI, or comparable technologies
• Experience with or a strong understanding of Model Context Protocol (MCP), function/tool calling, agent registries, and AI orchestration patterns
• Experience with modern AI coding assistants or autonomous development tools, such as Devin, Windsurf, or comparable solutions
• Familiarity with enterprise IT and infrastructure platforms, ideally including one or more of ServiceNow/CMDB, Dynatrace, Zabbix, and GCP
• Understanding of ITSM, incident management, observability, monitoring, infrastructure telemetry, or AIOps concepts
• Experience working with both structured and unstructured data and preparing enterprise information for AI consumption
• Understanding of AI safety, data governance, security, access control, grounding, hallucination mitigation, and responsible AI principles
• Experience designing or operating production systems where reliability, scalability, observability, and maintainability are important
• Strong systems-thinking and problem-solving skills, with the ability to understand complex enterprise environments and translate operational requirements into practical technical solutions
• Ability to collaborate effectively with architects, software engineers, infrastructure teams, IT operations, security, and other technical stakeholders
• Comfortable working iteratively, delivering measurable value through a phased approach from read-only AI assistance to controlled automation and ultimately agentic execution
• Participation in both internal meetings and external meetings via video calls, as necessary
• Ability to go into corporate or client offices to work onsite, as necessary
• Prolonged periods of remaining stationary at a desk and working on a computer, as necessary
• Ability to bend, kneel, crouch, and reach overhead, as necessary
• Hand-eye coordination necessary to operate computers and various pieces of office equipment, as necessary
• Vision abilities including close vision, toleration of fluorescent lighting, and adjusting focus, as necessary
• For positions that require business travel and/or event attendance, ability to lift 25 lbs, as necessary
• For positions that require business travel and/or event attendance, a valid driver's license and acceptable driving record are required, as driving is an essential job function

Qualifications

Must Haves

• 3–5 years of overall relevant engineering experience, combining modern AI engineering with a strong software, integration, data, infrastructure, or AIOps foundation
• Approximately 1–2 years of hands-on experience with Generative AI/LLMs, including building applications or workflows using modern LLM platforms
• Approximately 2–3 years of foundational engineering experience in one or more areas such as backend software development, Python engineering, API integration, data engineering, cloud engineering, automation, or AIOps
• Strong programming skills in Python, including experience developing production-quality backend services and automation
• Strong experience designing, building, and consuming RESTful APIs and integrating multiple enterprise systems
• Practical knowledge of LLMs, prompt engineering, context management, embeddings, vector retrieval, and Retrieval-Augmented Generation (RAG)
• Hands-on experience with agentic or multi-agent AI frameworks, such as LangChain/LangGraph, AutoGen, CrewAI, or comparable technologies
• Experience with or a strong understanding of Model Context Protocol (MCP), function/tool calling, agent registries, and AI orchestration patterns
• Experience with modern AI coding assistants or autonomous development tools, such as Devin, Windsurf, or comparable solutions
• Familiarity with enterprise IT and infrastructure platforms, ideally including one or more of ServiceNow/CMDB, Dynatrace, Zabbix, and GCP
• Understanding of ITSM, incident management, observability, monitoring, infrastructure telemetry, or AIOps concepts
• Experience working with both structured and unstructured data and preparing enterprise information for AI consumption
• Understanding of AI safety, data governance, security, access control, grounding, hallucination mitigation, and responsible AI principles
• Experience designing or operating production systems where reliability, scalability, observability, and maintainability are important
• Strong systems-thinking and problem-solving skills, with the ability to understand complex enterprise environments and translate operational requirements into practical technical solutions
• Ability to collaborate effectively with architects, software engineers, infrastructure teams, IT operations, security, and other technical stakeholders
• Comfortable working iteratively, delivering measurable value through a phased approach from read-only AI assistance to controlled automation and ultimately agentic execution
• Participation in both internal meetings and external meetings via video calls, as necessary
• Ability to go into corporate or client offices to work onsite, as necessary
• Prolonged periods of remaining stationary at a desk and working on a computer, as necessary
• Ability to bend, kneel, crouch, and reach overhead, as necessary
• Hand-eye coordination necessary to operate computers and various pieces of office equipment, as necessary
• Vision abilities including close vision, toleration of fluorescent lighting, and adjusting focus, as necessary
• For positions that require business travel and/or event attendance, ability to lift 25 lbs, as necessary
• For positions that require business travel and/or event attendance, a valid driver's license and acceptable driving record are required, as driving is an essential job function

Benefits

• Share plan
• Company performance bonuses
• Value-based recognition awards
• Referral bonus
• Career coaching
• Global career opportunities
• Non-linear career paths
• Internal development programmes for management and technical leadership
• Complex projects
• Rotations
• Internal tech communities
• Training
• Certifications
• Coaching
• Online learning platform subscriptions
• Pass-it-on sessions
• Workshops
• Conferences
• Hybrid work and flexible working hours
• Employee assistance programme
• Global internal wellbeing programme
• Access to wellbeing apps
• Global internal tech communities
• Hobby clubs and interest groups
• Inclusion and diversity programmes
• Events and celebrations
• For USA full-time roles only: robust healthcare and benefits including Medical, Dental, vision, Disability coverage, and various other benefit options
• For USA full-time roles only: Flexible Spending Accounts (Medical, Transit, and Dependent Care)
• For USA full-time roles only: Employer Paid Life Insurance and AD&D Coverages
• For USA full-time roles only: Health Savings account paired with our low-cost High Deductible Medical Plan
• For USA full-time roles only: 401(k) Safe Harbor Retirement plan with employer match with immediately vest