Senior Modernization Engineer (FDE)

Kyndryl; Bengaluru; On-site; INR 1,400,000 - 2,200,000; Full time

Job summary

Kyndryl is seeking a Forward Deployed Engineer to collaborate with customers and deliver real-world AI solutions. You will scope, prototype, and deploy production-ready systems in partnership with engineering, consulting, and product teams, often on-site, focusing on measurable business outcomes.

You'll work with Generative AI, agentic architectures, and multi-agent ecosystems, translating complex business requirements into practical technical implementations.

Qualifications

• Proficiency in Python or similar languages; experience with AI/ML frameworks is a plus.
• Familiarity with Hugging Face and open-source AI tools.
• Strong depth in one or two AI/ML/cloud domains with broad cross-functional knowledge.
• Experience designing or integrating multi-agent systems and orchestration frameworks.
• Practical knowledge of retrieval-augmented generation (RAG) knowledge systems.
• Solid software engineering practices, version control, and data engineering basics.
• Experience with cloud AI platforms (AWS/Azure/Google AI) and distributed architectures.
• Ability to translate business requirements into technical solutions and communicate value to stakeholders.
• Willingness to travel and work on customer premises.

Responsibilities

• Engage with customers to translate business challenges into high-quality AI solutions.
• Rapid prototyping of custom AI solutions using agentic AI frameworks.
• Own end-to-end delivery from scoping to production in a customer-team setting.
• Troubleshoot and optimize system performance, scalability, and reliability.
• Capture deployment learnings and contribute to platform improvements.
• Continuously learn and adapt to new technologies and customer requirements.
• Contribute to the evolution of AI platforms through feedback and collaboration with product teams.

Skills

Python

AI/ML frameworks (TensorFlow/PyTorch)

Hugging Face ecosystem

T-shaped profile across AI/ML, cloud,演

Agentic AI systems

RAG architectures

Git & GitHub

Cloud platforms (AWS/Azure/Google AI)

Performance & security practices

Business communication to execs

Willingness to travel

Education

Degree in Computer Science/Data Science/Engineering

Tools

LangGraph

Semantic Kernel

Agent frameworks (CrewAI, AutoGen)

Git

Pandas

Spark

TensorFlow

PyTorch

Job description

Job Summary

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

• 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.
• Rapid Prototyping: Build and iterate custom AI solutions tailored to customer needs, leveraging agentic AI frameworks.
• Ownership, Deployment Partnership: 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.
• Optimisation: Troubleshoot and enhance system performance, scalability, and reliability.
• Field Intelligence: Systematically capture deployment learnings, document best practices, and proactively share insights to inform enhancements to Kyndryl's core platforms and frameworks.
• Continuous Learning: Adapt quickly to emerging technologies and evolving customer requirements by engaging in ongoing professional development.
• Platform Contribution: Actively contribute to the evolution of Kyndryl's AI platforms through feedback, code contributions, and collaboration with product teams.

Required Skills and Experience

• Programming Proficiency: Demonstrable expertise in Python, (or another modern language such as C#, Node.js or TypeScript); experience working with AI/ML frameworks like TensorFlow or PyTorch is a plus.
• 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.
• Retrieval-Augmented Generation (RAG) Knowledge Systems: Practical knowledge of deploying RAG architectures and integrating structured and unstructured knowledge sources into AI solutions.
• Software Engineering: Solid grasp of the software delivery lifecycle, version control (Git GitHub), and data engineering tools such as Pandas and Spark.
• Cloud Distributed Systems: Experience with cloud AI platforms (AWS, Azure, Google AI) and distributed computing architectures.
• Performance Security: Knowledge of system-level optimisation and security best practices for scalable AI systems.
• Business Acumen: Ability to translate business requirements into technical solutions and communicate technical value to diverse stakeholders, including executive audiences.
• Flexibility: Willingness to travel and work on customer premises as required.
• Education: Degree-level qualification in Computer Science, Informatics, Data Science, Engineering, or a closely related discipline - or equivalent professional experience.

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