lead ai engineer

Auxo Talent

<div>
 
 
 Lead AI Engineer (AI/ML Engineering)
 
 
 
 
 
 
 
 Location:
 
 Dubai, UAE (Onsite)
 
 
 We are hiring a
 
 Lead AI Engineer
 
 to join a major enterprise organization building a next generation AI capability. This is a highly hands on engineering role focused on designing, building, and deploying
 
 production grade AI applications
 
 at enterprise scale.
 
 
 This is
 
 not
 
 a research or AI consulting role. We are looking for engineers who can take AI solutions from concept to production.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Design, develop, and deploy production AI applications
 </li>
 <li>
 Build scalable backend services, APIs, and AI workflows
 </li>
 <li>
 Develop LLM, RAG, and Agentic AI solutions
 </li>
 <li>
 Integrate AI capabilities into enterprise platforms
 </li>
 <li>
 Design production ready data pipelines and microservices
 </li>
 <li>
 Ensure scalability, reliability, security, and performance
 </li>
 <li>
 Collaborate with cross functional teams to deliver enterprise AI solutions
 </li>
 </ul>
 
 Mandatory Skills
 
 <ul>
 <li>
 Strong Python development
 </li>
 <li>
 FastAPI, Flask, or Django
 </li>
 <li>
 Backend API development and Microservices
 </li>
 <li>
 LLMs, RAG, LangChain, LangGraph, Agentic AI
 </li>
 <li>
 SQL/PostgreSQL
 </li>
 <li>
 Docker &amp; Kubernetes
 </li>
 <li>
 AWS, Azure, or GCP
 </li>
 <li>
 Production AI/ML deployment experience
 </li>
 <li>
 CI/CD, MLOps, or LLMOps
 </li>
 <li>
 Experience building end to end AI applications
 </li>
 </ul>
 
 Preferred Background
 
 <ul>
 <li>
 Software Engineering / Computer Science / Data Science
 </li>
 <li>
 Strong backend engineering foundation
 </li>
 <li>
 Experience in Logistics, Retail, FMCG, FinTech, Banking, or large enterprise environments
 </li>
 <li>
 Experience owning AI products from POC to Production
 </li>
 </ul>
 
 
 
</div>

Lead AI Engineer

Mastercard

<div>Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we&rsquo;re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Lead AI Engineer
Who is Mastercard? 
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payment choices, making transactions secure, simple, smart, and accessible. Our technology and innovation, partnerships, and networks combine to deliver a unique set of products and services that help people, businesses, and governments realize their greatest potential. 
Our decency quotient (DQ) drives our culture and everything we do inside and outside our company. We cultivate an environment where individuals can thrive, collaborate, and contribute to innovations that power the global economy. 
Overview 
The AI Platform Engineering team is responsible for building, operating, and evolving Mastercard's enterprise AI platforms and capabilities. Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams across Mastercard to accelerate the development and deployment of AI-powered solutions. 
As a Lead AI Engineer, you will help design, implement, and operate the foundational platforms that support AI and machine learning workloads across the enterprise. You will work at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations to deliver enterprise-grade capabilities that enable teams to safely develop, deploy, observe, and scale AI solutions. 
This team functions as an enterprise AI Platform Engineering organization, delivering and operating shared AI capabilities that enable application teams to build AI-powered products at scale across public and private cloud environments. 
The Role 
As a Lead AI Engineer, AI Platform Engineering, you will contribute to the architecture, engineering, automation, and operational excellence of Mastercard's AI platforms. You will collaborate with software engineers, data scientists, infrastructure teams, security partners, governance organizations, and business stakeholders to build scalable AI services that support a growing portfolio of AI use cases. 
The ideal candidate combines strong software engineering and cloud platform expertise with experience supporting AI and machine learning systems in production environments. You are passionate about automation, reliability, customer enablement, operational excellence, and building platforms that empower others to innovate. 
Responsibilities 
Design, build, and operate enterprise AI platforms supporting machine learning, generative AI, and advanced analytics workloads. 
Engineer scalable solutions across public and private cloud environments, ensuring security, reliability, availability, and performance. 
Build and automate platform capabilities that simplify onboarding, deployment, operations, and lifecycle management for AI solutions. 
Develop and maintain infrastructure, tooling, and services that support model training, evaluation, deployment, monitoring, and governance. 
Implement and enhance MLOps capabilities that enable repeatable, scalable, and secure AI development workflows. 
Design and maintain observability solutions, including telemetry, performance monitoring, logging, alerting, operational analytics, and drift detection. 
Support production AI platforms and services, proactively identifying opportunities to improve reliability, scalability, efficiency, and customer experience. 
Partner with internal engineering teams to understand requirements, enable platform adoption, and accelerate delivery of AI-powered products. 
Collaborate with infrastructure, security, architecture, and governance teams to ensure alignment with enterprise standards, controls, and regulatory requirements. 
Evaluate emerging AI technologies, platform capabilities, and industry trends to help shape the future direction of Mastercard's AI ecosystem. 
Drive automation and engineering best practices through Infrastructure as Code, CI/CD, testing, and operational excellence initiatives. 
Participate in troubleshooting, root cause analysis, operational support, and incident response activities to maintain highly available platforms. 
Contribute to technical design discussions, architecture reviews, and long-term platform strategy. 
Mentor peers and share knowledge across engineering teams while contributing to a culture of continuous improvement. 
All About You 
Required Qualifications 
Experience designing, building, and operating cloud-native systems in enterprise environments. 
Strong experience working within both public and private cloud environments. 
Experience deploying and managing containerized workloads using Kubernetes or OpenShift. 
Strong software engineering and automation experience using Python. 
Experience implementing CI/CD pipelines and modern DevOps practices. 
Experience supporting production AI, machine learning, data platforms, or large-scale distributed systems. 
Strong understanding of MLOps principles and machine learning lifecycle management. 
Experience implementing monitoring, observability, telemetry, logging, and operational analytics solutions. 
Strong troubleshooting, analytical, and problem-solving skills. 
Ability to communicate effectively with technical and non-technical stakeholders. 
Experience working in highly collaborative, cross-functional engineering environments. 
Preferred Qualifications 
Experience supporting generative AI platforms and large language model (LLM) workloads. 
Experience implementing model evaluation, finetuning, guardrails, and model governance controls. 
Experience with model observability, drift detection, telemetry monitoring, and operational analytics. 
Experience with AI serving infrastructure and inference platforms. 
Experience supporting GPU-based workloads and accelerated computing environments. 
Experience with OpenShift, Kubernetes, Docker, Helm, GitOps, and Infrastructure as Code practices. 
Experience with enterprise-scale platform engineering, developer enablement, and self-service platform capabilities. 
Familiarity with vector databases, retrieval systems, AI gateways, agentic systems, or emerging AI platform technologies. 
Experience working within regulated environments requiring strong security, governance, and compliance controls. 
Key Capabilities 
The successful candidate will demonstrate proficiency in: 
Public and Private Cloud 
Model Building, Observability, and Scaling 
MLOps (Machine Learning Operations) 
Drift Detection and Telemetry Data Monitoring 
Model Evaluation, Finetuning, and Guardrails 
Deep Learning and Neural Networks 
Iterative Model Development 
Hyperparameter Tuning 
Reinforcement Learning and Feedback Loops 
Python 
What Makes This Role Unique 
This role provides the opportunity to influence and operate the foundational AI platforms that enable innovation across Mastercard. Rather than focusing solely on individual AI models or applications, you will help build and scale the enterprise platforms, tooling, operational practices, and cloud infrastructure that support the next generation of AI capabilities across the organization. 
You will work on challenging problems involving platform scalability, reliability, observability, governance, automation, and customer enablement while helping shape Mastercard's long-term AI platform strategy.
Corporate Security Responsibility 
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:<ul><li>
Abide by Mastercard&rsquo;s security policies and practices;</li><li>
Ensure the confidentiality and integrity of the information being accessed;</li><li>
Report any suspected information security violation or breach, and</li><li>
Complete all periodic mandatory security trainings in accordance with Mastercard&rsquo;s guidelines.</li></ul></div>

Ocho

<div>
 
 
 Lead AI Engineer | Belfast (Remote-First) | AI Centre of Excellence
 
 
 
 
 
 
 
 At a Glance
 
 
 <ul>
 <li>
 Sits within a dedicated AI Centre of Excellence
 </li>
 <li>
 Stack: Azure, Python, React, Terraform
 </li>
 <li>
 Northern Ireland &ndash; Remote working
 </li>
 </ul>
 
 
 
 
 
 About the Company
 
 
 
 A large, well-established global technology company with a dedicated AI Centre of Excellence &mdash; a team set apart from its core consulting and digital services divisions, focused purely on applied research and product builds using the latest Microsoft AI technology.
 
 
 
 
 
 
 Role Overview
 
 
 
 You'll join a close-knit team of around 10-11 engineers (the majority in Belfast, with others in Poland, Birmingham, and London) as a Senior AI Engineer, providing technical leadership on AI-powered products and applied research work. This isn't a billable, consulting-style role &mdash; there's no utilisation target and no client delivery pressure. The team is genuinely AI-first: they're looking for strong, well-rounded engineers rather than candidates who tick every box, whether your background is more AI-shaped or more software-shaped.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Provide technical leadership and own architecture, planning, and delivery for AI-powered products and applied research projects
 </li>
 <li>
 Build and integrate AI/ML solutions &mdash; model integration, evaluation, prompt engineering, and RAG pipelines &mdash; using Azure AI services (Azure OpenAI, Microsoft Foundry, Cognitive Services)
 </li>
 <li>
 Design and develop across the full stack, from API design and data pipelines through to front-end integration
 </li>
 <li>
 Coach, mentor, and support the development of junior engineers within the team
 </li>
 <li>
 Drive modern CI/CD practice, including model versioning, experiment tracking, and automated evaluation for ML/AI workloads
 </li>
 </ul>
 
 
 
 
 
 What You'll Need
 
 
 
 
 Essential:
 
 
 <ul>
 <li>
 Strong hands-on experience in Python or C#/.NET, with real experience building AI/ML-powered products (model integration, evaluation, prompt engineering, or RAG)
 </li>
 <li>
 Technical experience &mdash; owning architecture, planning, and delivery for a product or project, with a track record of coaching and developing junior engineers
 </li>
 <li>
 Experience with Microsoft Azure AI services (Azure OpenAI Service, Microsoft Foundry, Cognitive Services) or an equivalent cloud AI platform
 </li>
 </ul>
 
 
 
 
 
 Desirable:
 
 
 <ul>
 <li>
 Familiarity with the Microsoft agent ecosystem &mdash; Microsoft Agent Framework, Copilot Studio, Microsoft 365 Agents SDK, or Semantic Kernel
 </li>
 <li>
 Understanding of responsible AI practice &mdash; content filtering, PII handling, bias testing, governance of autonomous agent actions
 </li>
 <li>
 Experience with vector databases or search indices, and broader public cloud platforms (Azure or AWS)
 </li>
 </ul>
 
 
 
 
 
 Benefits &amp; Package
 
 
 <ul>
 <li>
 &pound; DOE
 </li>
 <li>
 Fully remote-first NI Wide &mdash; no mandatory office days, with an optional Wednesday in-office and roughly monthly full-team get-togethers
 </li>
 <li>
 Straightforward two-stage interview process &mdash; culture and skills, then a technical deep dive &mdash; no take-home assessment
 </li>
 </ul>
 
 
 
 
 Get in touch with Colin directly at colin@ochopeople.com
 
 
 
 
</div>

<div>
 
 
 About the Company:
 
 
 
 E2M Solutions works as a trusted white-label partner for digital agencies. We support agencies with consistent and reliable delivery through services such as website design, web development, eCommerce, SEO, AI SEO, PPC, AI automation, and content writing. Founded on strong business ethics, we are an equal opportunity organization powered by 300+ experienced professionals, partnering with 400+ digital agencies across the US, UK, Canada, Europe, and Australia. At E2M, we value ownership, consistency, and people who are committed to doing meaningful work and growing together. If you&rsquo;re someone who dreams big and has the gumption to make them come true, E2M has a place for you.
 
 
 
 
 
 
 About the Role:
 
 
 
 We are seeking a highly skilled Technical Lead &ndash; AI who combines deep technical expertise in AI/ML with strong leadership capabilities. The ideal candidate will be responsible for designing AI architectures, leading development teams, and ensuring the successful implementation of AI-driven solutions. This role requires a hands-on technical leader who can guide engineers, solve complex AI problems, and collaborate with cross-functional teams to translate business needs into innovative AI solutions.
 
 
 
 
 
 
 Responsibilities:
 
 
 
 
 Technical Leadership:
 
 
 <ul>
 <li>
 Lead the design and development of AI/ML solutions and intelligent automation systems.
 </li>
 <li>
 Provide technical guidance and mentorship to AI engineers and developers.
 </li>
 <li>
 Conduct architecture reviews, code reviews, and technical evaluations.
 </li>
 <li>
 Ensure adoption of best practices in coding and app development.
 </li>
 </ul>
 
 
 
 
 
 AI Solution Development:
 
 
 <ul>
 <li>
 Develop AI-powered solutions such as chatbots, recommendation engines, NLP systems, and predictive analytics models.
 </li>
 <li>
 Work on LLM-based applications, prompt engineering, and AI workflow automation.
 </li>
 <li>
 Build scalable AI APIs and production-ready AI systems.
 </li>
 </ul>
 
 
 
 
 
 Innovation &amp; Research:
 
 
 <ul>
 <li>
 Stay updated with the latest advancements in AI, Machine Learning, and Generative AI technologies.
 </li>
 <li>
 Evaluate new tools, frameworks, and technologies to enhance AI capabilities within the organization.
 </li>
 <li>
 Contribute to internal AI initiatives and innovation projects.
 </li>
 </ul>
 
 
 
 
 
 Required Experience/Qualification:
 
 
 <ul>
 <li>
 Overall 4&ndash;8 years of experience in AI/ML development including minimum 2+ years in a Technical Lead / Senior Engineer role.
 </li>
 <li>
 Proven experience in building production-level AI applications.
 </li>
 <li>
 Experience in leading or mentoring a team of engineers.
 </li>
 <li>
 Background in service-based or product engineering companies preferred.
 </li>
 </ul>
 
 
 
 
 
 Required Skills:
 
 
 <ul>
 <li>
 Experience working with Generative AI and Large Language Models (LLMs).
 </li>
 <li>
 Experience with Lang Chain, Llama Index, or similar AI orchestration frameworks.
 </li>
 <li>
 Strong knowledge of Natural Language Processing (NLP).
 </li>
 <li>
 Experience building AI APIs and integrating AI into applications.
 </li>
 <li>
 Familiarity with vector databases, embeddings, and RAG architectures.
 </li>
 <li>
 Working knowledge of Full Stack development.
 </li>
 </ul>
</div>

Jade Global

<div><div>Technical Skills
<ul><li>Engineering Stack: Strong hands-on proficiency in Python and/or .NET (C#, ASP.NET Core) , Java , or Node.js .
</li><li>AI &amp; GenAI: Practical experience with GenAI APIs (OpenAI, Azure OpenAI), LangChain, LlamaIndex, RAG patterns, or agentic workflow frameworks.
</li><li>Cloud &amp; DevOps: Hands-on experience with AWS, Azure, or GCP&mdash;microservices, Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Azure DevOps).
</li><li>Automation: Exposure to workflow orchestration engines, RPA tools, or custom automation scripts.
</li><li>Enterprise Platforms: Familiarity with enterprise systems (Oracle, SAP, Salesforce, or ServiceNow) is a plus.
</li><li>Certifications: Cloud Certification (AWS, Azure, or GCP) at associate/developer level is a plus.
</li></ul>Soft Skills
<ul><li>Clear technical communication&mdash;able to explain code implementation to teammates and project managers.
</li><li>Collaborative team player accustomed to working across global/offshore time zones.
</li><li>Curious and self-motivated &mdash; proactively explores new AI tools, frameworks, and engineering patterns.
</li></ul>Experience
<ul><li>Experience: 5&ndash;8 years of hands-on software engineering experience, with 3+ years as, Senior AI engineer 
 
</li><li>Hands-on experience building and delivering enterprise-grade solutions across cloud, AI/ML, and application engineering. 
 
</li><li>Experience working in client-facing delivery environments within IT services or consulting organizations is preferred. 
</li></ul><h2 class="jobSectionHeader">Key Responsibilities
</h2><h3 class="jobSectionHeader">1. Hands-on Engineering &amp; Delivery
</h3><ul><li>Write production-grade code to build component-level features and API integrations based on technical designs and blueprints.
</li><li>Actively contribute to daily engineering deliverables&mdash;developing backend microservices, driving unit testing, refactoring code, and resolving technical debt.
</li><li>Conduct peer code reviews to ensure code quality, performance, maintainability, and adherence to team engineering standards.
</li><li>Troubleshoot and resolve complex bugs, API integration issues, and performance bottlenecks within application microservices.
</li></ul>AI &amp; Engineering Framework Adoption
<ul><li>Learn, implement, and integrate for AI-native feature&mdash; including GenAI integration patterns, agentic workflows, and intelligent automation
</li><li>Contribute to the development and maintenance of AI engineering frameworks, solution accelerators, and reusable technical assets. 
 
</li><li>Evaluate and experiment with new tools, APIs, and platforms in the AI and cloud-native space.
</li></ul>Technical Consulting &amp; Problem Solving
<ul><li>Engage with client technical teams to understand system landscapes, integration requirements, and technical constraints. 
 
</li><li>Propose pragmatic, technology-forward solutions to complex engineering challenges across application modernization, AI integration, and cloud migration. 
 
</li><li>Support the Solution and Principal Architect in pre-sales activities including technical assessments, proof-of-concept design, and effort estimation.
</li></ul><h3 class="jobSectionHeader">Cloud &amp; Automation Execution
</h3><ul><li>Develop and deploy cloud-native services on AWS, Azure, or GCP using containers (Docker, Kubernetes), serverless functions, and event-driven patterns.
</li><li>Implement intelligent automation components using workflow orchestration engines, RPA integrations, or custom AI-driven pipelines.
</li></ul>Engineering Community &amp; Mentoring
<ul><li>Mentor junior engineers&mdash;supporting technical upskilling on AI tools, cloud platforms, and modern engineering practices. 
 
</li><li>Contribute to Jade's internal community of practice through knowledge sharing, documentation, and participation in architecture discussions.
</li></ul>Education
<ul><li>Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related technical field is required .</li></ul></div></div>

S&P Global

<div>
 
 About The Role
 
 
 
 
 Grade Level (for internal use):
 
 
 
 11
 
 
 
 Lead AI Engineer (Agentic Systems)
 
 
 
 
 Role Summary
 
 
 
 As the Lead AI Engineer (Agentic Systems), you will help architect and build the organization&rsquo;s next generation of autonomous AI workflows. This is a multidisciplinary technical role operating at the intersection of Software Engineering, Data Engineering, and Machine Learning Engineering. You will move beyond simple "chatbots" to design production-grade Agentic Systems: intelligent applications capable of reasoning, planning, and executing complex tasks autonomously.
 
 
 
 Responsibilities
 
 
 
 
 Agentic Systems Architecture &amp; Core Engineering
 
 
 
 <ul>
 <li>
 Architect &amp; Build Multi-Agent Workflows: Lead the hands-on design and coding of stateful, production-grade agentic systems using Python and orchestration frameworks like LangGraph, CrewAI, or AutoGen.
 </li>
 <li>
 Agent-to-Agent (A2A) Communication: Design and implement robust A2A protocols enabling autonomous agents to collaborate, hand off sub-tasks, and negotiate execution paths dynamically within multi-agent environments.
 </li>
 <li>
 State Management &amp; Orchestration: Engineer robust control flows for non-deterministic agents; implement complex message passing, memory persistence, and interruptible state handling to support long-running autonomous tasks.
 </li>
 <li>
 Tool Interface Design (MCP): Implement and standardize the Model Context Protocol (MCP) to create universal interfaces between agents, data sources, and operational tools, ensuring modularity and scalability.
 </li>
 <li>
 Model Integration &amp; Optimization: Utilize proxy services (i.e. LiteLLM) to manage model routing and fallback strategies; optimize context windows and inference costs across proprietary and open-source models.
 </li>
 <li>
 Production Deployment: Containerize agentic workloads using Docker and orchestrate deployments on Kubernetes; leverage AWS AgentCore or similar cloud-native services for scalable infrastructure.
 
 
 </li>
 </ul>
 
 Data Engineering &amp; Operational Real-Time Integration
 
 
 
 <ul>
 <li>
 Build Agent Data Pipelines: Write and maintain high-throughput ingestion pipelines (using Databricks or Python-based ETL) that transform raw operational signals into structured context for agents.
 </li>
 <li>
 Real-Time Context Injection: Ensure agents have access to "operational real-time" data (seconds/minutes latency) by optimizing retrieval architectures and vector store performance.
 </li>
 <li>
 Cross-Functional Engineering: Act as the technical bridge between Data Engineering and AI teams; translate complex agent requirements into concrete data schemas and pipeline specifications, while stepping in to resolve hands-on bottlenecks in data availability.
 
 
 </li>
 </ul>
 
 Observability, Governance &amp; Human-in-the-Loop
 
 
 
 <ul>
 <li>
 LLMOps &amp; Tracing: Implement comprehensive observability using tools like Langfuse to trace agent reasoning steps, monitor token usage, and debug latency issues in production.
 </li>
 <li>
 Safety &amp; Control Frameworks: Design hybrid execution modes ranging from Human-in-the-Loop (HITL) for sensitive operations to fully autonomous execution; build "break-glass" mechanisms and guardrails for automated decision-making.
 </li>
 <li>
 Evaluation &amp; Reliability: Establish technical standards for testing non-deterministic outputs; automate evaluation pipelines to measure agent accuracy, hallucination rates, and drift before deployment.
 
 
 </li>
 </ul>
 
 Technical Leadership &amp; Strategy
 
 
 
 <ul>
 <li>
 Technical Roadmap Definition: Partner with Product and Engineering leadership to scope feasibility for autonomous projects; define the "Agentic Architecture" roadmap.
 </li>
 <li>
 Mentorship &amp; Standards: Define code quality standards, architectural patterns, and PR review processes for the AI engineering team; upskill team members on the latest agentic frameworks and methodologies.
 </li>
 <li>
 Innovation: Proactively prototype with emerging tools (e.g., new reasoning models, graph-based RAG) to solve high-value business problems, moving successful experiments into the production roadmap.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Required
 
 
 
 <ul>
 <li>
 Experience: 7+ years of total technical experience in Software Engineering, Data Engineering, or Machine Learning.
 </li>
 <li>
 GenAI Specialization: 2+ years of specific experience building and deploying LLM-based applications or Agentic Systems in production.
 </li>
 <li>
 Database &amp; Lakehouse Mastery: Experience architecting storage layers for AI, including Vector Databases (e.g., Pinecone, Weaviate, Qdrant), NoSQL/Relational Databases (PostgreSQL, DynamoDB), and modern Data Lakehouses (specifically Databricks or Snowflake).
 </li>
 <li>
 Cloud &amp; Infrastructure: Expertise in cloud architecture and container orchestration (AWS, GCP, or Azure) using Kubernetes and Docker. You must be comfortable deploying and scaling your own applications.
 </li>
 <li>
 LLM Ecosystem: Familiarity with common LLM frameworks and orchestration libraries (e.g., LangGraph, LangChain, CrewAI, AutoGen). You understand the mechanics of RAG, embeddings, and context window management.
 </li>
 <li>
 Hybrid Engineering Skillset: A unique blend of Data Science (understanding model behavior, probability, and prompting) and Software Engineering (CI/CD, API design, asynchronous programming, and system reliability).
 </li>
 <li>
 Language Proficiency: Advanced proficiency in Python for systems engineering, capable of writing modular, testable, and maintainable production code.
 </li>
 <li>
 Education: Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, or a related technical field.
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Advanced Education: Master&rsquo;s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
 </li>
 <li>
 NLP Expertise: 5+ years of hands-on experience in Natural Language Processing (NLP), ranging from foundational techniques (e.g., text processing, embeddings, classification) to modern architectures.
 </li>
 <li>
 Graph Technologies: Experience with Knowledge Graphs (e.g., Neo4j, AWS Neptune), Graph Databases, and GraphML (Graph Machine Learning) to support complex reasoning and relationship modeling.
 </li>
 <li>
 Agentic Tooling: Specific experience with LangGraph, LiteLLM, Langfuse, AWS AgentCore, or implementing the Model Context Protocol (MCP).
 </li>
 <li>
 Advanced Architectures: Proven track record of implementing Agent-to-Agent (A2A) communication, swarm intelligence, or multi-modal agent workflows.
 </li>
 <li>
 Real-Time Operations: Experience working in environments requiring operational real-time processing (e.g., FinTech, Energy, Logistics).
 
 
 </li>
 </ul>
 
 Why This Role Matters
 
 
 
 You won't just be building chatbots here; you will be architecting the organization&rsquo;s "central nervous system." As the Lead AI Engineer for Agentic Systems, you are bridging the gap between static data models and active decision-making. The autonomous workflows you design&mdash;capable of planning, collaborating (A2A), and executing tasks&mdash;will fundamentally change how we operate, moving us from human-dependent processes to self-healing, intelligent systems. This is a rare opportunity to define the standards for Agentic AI in a production environment, working with a stack that represents the absolute cutting edge of the industry.
 
 
 
 About S&amp;P Global Energy
 
 
 
 At S&amp;P Global Energy, our comprehensive view of global energy and commodities markets enables our customers to make superior decisions and create long-term, sustainable value. Our four core capabilities are: Platts for news and pricing; CERA for research and advisory; Horizons for energy expansion and sustainability solutions; and Events for industry collaboration.
 
 
 S&amp;P Global Energy is a division of S&amp;P Global (NYSE: SPGI). S&amp;P Global enables businesses, governments, and individuals with trusted data, expertise, and technology to make decisions with conviction. We are Advancing Essential Intelligence through world-leading benchmarks, data, and insights that customers need in order to plan confidently, act decisively, and thrive economically in a rapidly changing global landscape. Learn more at www.spglobal.com/energy.
 
 
 
 What&rsquo;s In It For
 
 
 You?
 
 
 
 
 Our Mission
 
 
 
 Advancing Essential Intelligence.
 
 
 
 Our People
 
 
 
 We're more than 35,000 strong worldwide&mdash;so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We&rsquo;re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.
 
 
 
 Our Values
 
 
 
 
 Integrity, Discovery, Partnership
 
 
 
 Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
 
 
 
 Benefits
 
 
 
 We take care of you, so you can take care of business. We care about our people. That&rsquo;s why we provide everything you&mdash;and your career&mdash;need to thrive at S&amp;P Global.
 
 
 
 Our Benefits Include
 
 
 
 <ul>
 <li>
 Health &amp; Wellness: Health care coverage designed for the mind and body.
 </li>
 <li>
 Flexible Downtime: Generous time off helps keep you energized for your time on.
 </li>
 <li>
 Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
 </li>
 <li>
 Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
 </li>
 <li>
 Family Friendly Perks: It&rsquo;s not just about you. S&amp;P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
 </li>
 <li>
 Beyond the Basics: From retail discounts to referral incentive awards&mdash;small perks can make a big difference.
 
 
 </li>
 </ul>
 For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries
 
 
 
 Global Hiring And Opportunity At S&amp;P Global
 
 
 
 At S&amp;P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.
 
 
 
 Recruitment Fraud Alert
 
 
 
 If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&amp;P Global never requires any candidate to pay money for job applications, interviews, offer letters, &ldquo;pre-employment training&rdquo; or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here.
 
 
 
 Equal Opportunity Employer
 
 
 
 S&amp;P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.
 
 
 If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.
 
 
 
 US Candidates Only:
 
 Know Your Rights: Workplace discrimination is illegal
 
 
 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.2 - Middle Professional Tier II (EEO Job Group), SWP Priority &ndash; Ratings - (Strategic Workforce Planning)
 
 
 
 Job ID:
 
 321035
 
 
 
 Posted On:
 
 2026-08-21
 
 
 
 Location:
 
 Gurgaon, Hary&amacr;na, India
</div>

Lead AI Engineer (Agentic Systems)

Nicholson Glover

<div>
 
 
 Lead AI Engineer | AI Tech Start-Up | &pound;100,000-&pound;130,000 DOE + Shares | London / Hybrid (1 Day Office)
 
 
 
 
 
 
 We&rsquo;re partnering with a fast-growing AI tech scale-up expanding its team, who are hiring for a Lead AI Engineer.
 
 
 
 
 
 This is a rare opportunity to lead the delivery of enterprise-grade Agentic AI solutions - working with ambitious clients at the forefront of applied AI innovation.
 
 
 
 
 
 
 The Company
 
 
 
 
 
 
 This pioneering organisation has built an advanced enterprise AI platform delivering predictive analytics and AI-powered decision intelligence.
 
 
 
 
 
 Their digital AI agents provide always-on, intelligent insights - supporting leading clients across financial services, retail, FMCG, pharma, and beyond to enhance performance and efficiency.
 
 
 
 
 
 
 The Role
 
 
 
 
 
 
 As Lead AI Engineer, you&rsquo;ll lead the delivery of Agentic AI solutions post-sale, owning client projects from design through to deployment. This is a hands-on role combining strong technical depth with delivery leadership and stakeholder management.
 
 
 
 
 
 You&rsquo;ll implement AI and agentic systems across enterprise clients, designing scalable architectures using LLMs, RAG pipelines, and agentic workflows, while working closely with engineering and product teams to ensure successful outcomes.
 
 
 
 
 
 
 The Candidate
 
 
 
 
 
 
 Key attributes of the suitable Lead AI Engineer include:
 
 
 
 
 <ul>
 <li>
 
 Technical Data Science Expertise
 
 &ndash; Strong background delivering production-grade solutions, ideally within consulting or product-led environments.
 </li>
 <li>
 
 Agentic AI &amp; Modern AI Systems
 
 Experience &ndash; Hands-on exposure to LLMs, RAG pipelines, and agentic
 </li>
 <li>
 
 Delivery Leadership &amp; Client Ownership
 
 &ndash; Comfortable leading teams while remaining technically involved and managing client relationships post-sale
 </li>
 </ul>
 
 
 
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