Mod Engineer (FDE)
Who We Are
The Role
Your Role
- Work closely with strategic customers as a Forward Deployed Engineer to solve complex technical challenges and deliver measurable business outcomes.
- Combine engineering, consulting and product expertise to shape practical solutions, with a strong focus on AI adoption and modernization delivery.
- Own delivery from scoping and prototyping through implementation, production rollout, adoption and optimization.
- Use Generative AI, Agentic AI and multi-agent technologies to create business value in complex enterprise environments.
- Act as a trusted technical partner who connects hands-on engineering excellence to customer outcomes.
Client Discovery
- Work directly with customers to understand business challenges, operating constraints, current-state workflows and desired outcomes.
- Translate ambiguous requirements into structured technical solutions, prototypes, implementation plans and adoption paths.
- Facilitate working sessions with customer stakeholders, product teams, engineering teams and consulting teams.
- Capture field learnings, blockers, best practices and opportunities to improve reusable Kyndryl platforms, playbooks and delivery assets.
Build & Delivery
- Design, build and iterate custom AI and modernization solutions using modern software engineering practices.
- Develop agentic workflows, RAG-enabled solutions, API integrations, enterprise automation patterns and production-ready prototypes.
- Lead end-to-end delivery from scope definition through production deployment, adoption, troubleshooting and optimization.
- Validate system performance, scalability, reliability, security and guardrails before and after deployment.
- Maintain clear documentation of architecture decisions, dependencies, runbooks, design choices and reusable delivery patterns.
AI Engineering
- Apply Generative AI, Agentic AI, multi-agent systems and orchestration frameworks to solve customer problems at enterprise scale.
- Integrate AI systems with enterprise APIs, cloud platforms, data stores, knowledge sources, vector databases and operational workflows.
- Contribute feedback, code, patterns and field intelligence to Kyndryl platforms, frameworks, agent catalogs and reusable accelerators.
- Continuously learn emerging AI, cloud and engineering capabilities and apply them to proposals, prototypes and delivery engagements.
Your future at Kyndryl Every position at Kyndryl offers a way forward to grow your career, from Junior System Administrator to Architect. We have opportunities for Cloud Hyperscalers that you won’t find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. One of the benefits of Kyndryl is that we work with clients in a variety of industries, from banking to retail. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.
Who You Are
Required Skills and Experience
- Hands-on development experience in Python or modern languages such as C#, Node.js or TypeScript.
- Strong software engineering fundamentals across SDLC, Git/GitHub, APIs, backend services, automated testing, CI/CD and secure engineering practices.
- Experience designing, building or integrating AI solutions using frameworks or tools such as LangChain, LangGraph, Semantic Kernel, Microsoft Agent Framework, AutoGen, CrewAI or equivalent.
- Understanding of AI/ML frameworks and open-source AI tools such as TensorFlow, PyTorch, Hugging Face or comparable technologies.
- Knowledge of RAG architectures, prompt engineering, structured and unstructured knowledge sources, SQL/NoSQL databases and vector databases.
- Experience with cloud platforms, containers and distributed systems, including Azure, AWS or GCP, Docker and Kubernetes.
- Ability to validate and improve performance, scalability, reliability, observability, data protection and security of AI-enabled solutions.
- Strong consulting and stakeholder skills, including business problem framing, executive communication and translation of requirements into technical outcomes.
- T-shaped profile with broad understanding of AI/ML, cloud, data, consulting and delivery, plus deep expertise in one or two areas.
- Ability to operate in ambiguous, fast-moving environments with ownership, curiosity and a continuous-learning mindset.
Preferred Skills and Experience
- Degree in Computer Science, Informatics, Data Science, Engineering or a related field, or equivalent practical experience.
- Real project experience implementing, operating and improving AI, Generative AI, Agentic AI or multi-agent solutions in production environments.
- Experience building full-stack prototypes or production systems using frontend, backend, API, data and cloud services.
- Experience with agent telemetry, observability, evaluation frameworks, guardrails, policy-as-code, knowledge graphs or semantic knowledge layers.
- Experience integrating AI solutions into enterprise systems such as APIs, workflows, data platforms, knowledge repositories and cloud services.
- Experience working with customers in regulated or mission-critical environments where reliability, security and compliance are essential.
- Experience contributing reusable assets, reference implementations, solution patterns, code libraries, delivery playbooks or platform improvements.
Being You
What You Can Expect
Get Referred!
Not included in the source posting: benefits.
Skills
Who can apply
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