Forward Deployed Engineer - AI Solutions

At Kyndryl, we deploy AI innovation where it creates the greatest real-world impact. As a Forward Deployed Engineer, you will collaborate directly with customers to solve complex challenges, shaping solutions that redefine industries. You will be empowered to work at speed, supported by a global AI ecosystem, and play a pivotal role in delivering outcomes that matter. This position operates within our triad delivery model, where engineering, consulting, and product expertise come together to drive transformative results for customers.

This is not traditional consulting or pure software engineering; it is a hybrid role designed for the complexities of real-world AI deployment, with accountability for outcomes not just code.

You will blend deep engineering expertise with consultative engagement to deliver tailored solutions that drive measurable business value. Operating in dynamic environments and working closely with customer teams - often on-site - you will scope, prototype, and deploy solutions at pace. Technologies include Generative AI, Agentic AI architectures, and multi-agent ecosystems, with insights continually fed back into Kyndryl’s platforms and frameworks to accelerate future deployments.

If you are motivated by solving complex problems, excel in direct customer engagement, and aspire to shape the future of enterprise AI, this role is designed for you.

Key Responsibilities 

• Build autonomous agents using LLMs, planning algorithms, and decision-making frameworks. 

• Implement agent architectures that support autonomy, interactivity, and task completion. 

• Integrate agents into applications, APIs, and workflows (e.g., copilots, chatbots, automation tools). 

• Connect agents to external services via APIs, databases, and cloud platforms. 

• Tune agent behavior using feedback loops, reinforcement learning, semantic knowledge layer and user interaction. 

• Monitor performance and implement safety, reliability, and guardrail mechanisms. 

• Work cross-functionally with researchers, engineers, and product teams. 

• Maintain clear documentation of agent logic, design decisions, and dependencies. 

• Build and maintain the Enterprise Agents and Tools Registry for metadata and lifecycle management. 

• Implement the Agent Communication Gateway with robust security, rate limits, observability, and cost controls. 

• Familiarity with AI Agent orchestration patterns and workflow orchestration engines (e.g., Temporal, Airflow, etc.). 

• Ensure agent-level security, including authentication, authorization, and data protection. 

• Optimize cost, scalability, performance, and reliability of agent operations across cloud and on-prem environments. 

• Familiarity with knowledge graphs for agent reasoning and data integration. 

• Deploy and customize agentic AI platforms (e.g., LLM agents, orchestration frameworks). 

• Integrate AI systems with enterprise APIs, data platforms, and workflows. 

• Solve technical blockers across data ingestion, model deployment, and agent behavior. 

• Design and refine prompts to ensure clarity, compliance, and contextual accuracy. 

• Translate business logic into agentic workflows and task trees. 

• Tune agent behavior to align with real-world expectations. 

• Implement observability tools to ensure reliability, latency, and trustworthiness. 

• Maintain performance metrics and feedback loops for continuous improvement. 

• Build and iterate custom AI solutions tailored to customer needs, leveraging agentic AI frameworks 

• Own delivery end to end, from scoping to production. Working as part of the customer team to engineer and deploy production‑ready solutions that drive adoption and measurable business outcomes. 

• Actively contribute to the evolution of Kyndryl’s AI platforms through feedback, code contributions, and collaboration with product teams 

• Customer Engagement & Solution Integrity: Partner with customers to understand business challenges and translate them into high‑quality, fit‑for‑purpose technical solutions, prioritising the right outcome over the fastest one. 

• Bachelor’s degree in computer science, Engineering, or equivalent. 

• Hands-on experience with Python development and frontend UI technologies (e.g., TypeScript, React.js, etc.) to build demos/systems from scratch as a full stack engineer.  

• Hands-on experience building AI based solutions using AI frameworks such as LangChain, Microsoft Semantic Kernel, Google ADK or Microsoft Agent Framework. 

• Knowledge of LLMs, AI Agent architectures, Agent Telemetry/Observability frameworks (Langsmith, Langfuse, litellm etc). 

• Expertise with Docker, Kubernetes, and at least one cloud platform (Azure, AWS, GCP) or on premises. 

• Experience in microservices-based architectures. 

• Solid grasp of the software delivery lifecycle, version control (Git & GitHub), and data engineering tools such as Pandas and Spark 

• Experience with cloud AI platforms (AWS, Azure, Google AI) and distributed computing architectures. 

• Ability to translate business requirements into technical solutions and communicate technical value to diverse stakeholders, including executive audiences. 

• Hands-on experience with SQL (e.g., PostgreSQL), NoSQL (e.g., MongoDB), and vector databases for agent data storage, semantic queries and retrieval. 

• Proficiency in CI/CD (e.g., GitHub Actions), automated testing, and observability. 

• Proficiency in API development, backend services, and cloud platforms (AWS, Azure, GCP). 

• Practical knowledge of deploying RAG architectures and integrating structured and unstructured knowledge sources into AI solutions. 

• Open-Source Ecosystems: Familiarity with community-driven AI tools and libraries, including Hugging Face and relevant repositories. 

• T-shaped Profile: Deep technical expertise in one or two domains, with broad understanding across AI/ML, cloud, and consulting. 

• Agentic AI Systems: Experience designing, building, or integrating multi-agent systems and orchestration frameworks (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI), including the development of agent protocols and coordination mechanisms. 

• Performance & Security: Knowledge of system-level optimisation and security best practices for scalable AI systems. 

• Willingness to travel up to 25% globally. 

 
Why join us? 
You will become part of a team that values pace, autonomy, and tangible impact. At Kyndryl, you will have full visibility of the delivery lifecycle, with opportunities to lead engagements and shape strategic direction. Our triad delivery model means you will work alongside experts in engineering, product, and consulting, fostering continuous learning and innovation. Career progression is clearly defined, from Junior to Principal levels, with pathways to influence the evolution of our AI platforms. You will contribute directly to platform development and see the results of your work in real-world applications. If you are seeking an environment where your ideas are valued and execution drives results, this is the place to make a difference. 
If you want to work where innovation meets execution, apply now.