Lead Engineer – Artificial Intelligence, Machine Learning

FIS

. Design and build generative artificial intelligence applications using proprietary and open-weight large language models .

Posted 10/12/2026full-timePune • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building generative artificial intelligence applications using large language models, with strong proficiency in Python and experience in agent-based systems and workflows. Capable of integrating AI solutions with enterprise platforms and evaluating model performance for accuracy and reliability.

Highest-signal resume keywords

Generative Artificial IntelligenceLarge Language ModelsAgent-Based SystemsPython ProgrammingMachine Learning Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative Artificial IntelligenceLarge Language ModelsAgent-Based SystemsPython ProgrammingMachine Learning FrameworksFlaskFastAPIVector DatabasesRetrieval-Augmented GenerationPrompting Techniques

Tools & Technologies

Amazon Web ServicesGoogle CloudMicrosoft AzureScikit-learnTensorFlowPyTorchKerasPandasLangChainOpenAI Assistants API

Industry Keywords

Artificial IntelligenceAgentic WorkflowsHuman-in-the-LoopContinuous IntegrationData Governance

Tech Stack

Tools & technologies

AWSAzureCloudFlaskKerasPandasPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Design and build generative artificial intelligence applications using proprietary and open-weight large language models
Develop agent-based systems and workflows supporting planning, memory, tool use, orchestration, human oversight and autonomous tasks
Integrate artificial intelligence solutions with enterprise platforms, application programming interfaces and business workflows
Build and deploy representational state transfer services using Flask or FastAPI
Evaluate model, agent and system performance, including accuracy, reliability, grounding and safety
Help turn emerging technologies into practical solutions applied across the organization
Collaborate within a team of solution architects, data scientists and machine learning engineers

Requirements

What you’ll need

At least 10 years of overall professional experience, including at least four years working with artificial intelligence, generative artificial intelligence or agent-based artificial intelligence
Experience designing and building GenAI-powered applications using open and proprietary LLMs
Experience building agent-based systems with planning, memory, tool use, and orchestration
Experience implementing agentic workflows, including multi-agent, human-in-the-loop, and autonomous tasks
Hands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation
Strong proficiency in Python
Experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas
Experience with vector databases and retrieval systems
Experience with cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure
Experience with services built with Flask or FastAPI
Bachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience
Preferred: experience fine-tuning LLMs, including parameter-efficient approaches such as low-rank adaptation and quantized low-rank adaptation
Preferred: familiarity with LangChain, LlamaIndex, AutoGen or the OpenAI Assistants API
Preferred: knowledge of production machine learning operations, continuous integration and delivery, monitoring, observability, security, compliance and data governance

Benefits

Comp & perks

Opportunities to make an impact in fintech
Internal career growth opportunities
Personal and professional learning
Inclusive, diverse work environment
Resources to give back to your community