Mod Engineer – FDE

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Kyndryl

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2021

🏢 Enterprise

🔒 Cybersecurity

☁️ SaaS

Enterprise • Cybersecurity • SaaS

Kyndryl is a leading IT infrastructure services provider, serving thousands of enterprise customers worldwide. The company specializes in designing, building, managing, and modernizing complex, mission-critical information systems. Kyndryl offers a range of services including IT consulting, cloud services, cybersecurity, data and AI solutions, and digital workplace transformation. With a strong focus on innovation, partnerships, and co-creation, Kyndryl helps businesses tackle IT complexity and drive operational excellence. The company operates across various industries such as automotive, healthcare, banking, and more, providing expertise and solutions to address industry-specific challenges. Kyndryl's global network and strategic alliances empower enterprises to adapt to the evolving technology landscape, ensuring their essential systems are reliable and efficient.

📋 Description

• Collaborate directly with customers to solve complex challenges • 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 • 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 • 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 • 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 • Actively contribute to the evolution of Kyndryl’s AI platforms through feedback, code contributions, and collaboration with product teams

🎯 Requirements

• 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.) • 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 • Familiarity with community-driven AI tools and libraries, including Hugging Face and relevant repositories • Experience designing, building, or integrating multi-agent systems and orchestration frameworks (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI) • Knowledge of system-level optimisation and security best practices for scalable AI systems • Willingness to travel up to 25% globally

🏖️ Benefits

• Flexible, supportive environment • Well-being prioritization • Career progression defined from Junior to Principal levels • Access to cutting-edge learning opportunities • Professional development through certifications and coaching