Senior AI Engineer

Grid Dynamics; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Medical insurance

Sports benefits

Flexible schedule

Professional development

Corporate events

Job summary

Grid Dynamics seeks an experienced AI/ML Data Scientist Contractor in Bengaluru to design, build, and deploy advanced predictive analytics, AI-driven decision-support, and agentic systems. You will collaborate with stakeholders, software engineers, and data teams to transform enterprise data into scalable forecasting and optimization capabilities.

The role covers problem definition, data engineering, model development, deployment, monitoring, and continuous improvement in production

Qualifications

• Strong quantitative data science skills with production AI experience.
• Ability to partner with business stakeholders, software engineers, and data teams.

Responsibilities

• Design, develop, and deploy predictive models for forecasting and optimization.
• Develop ML solutions using structured, semi-structured, and unstructured data.
• Create statistical models to improve forecasting accuracy and support decisions.
• Build explainable models and communicate drivers, assumptions, risks, and confidence intervals.
• Develop production-grade ML pipelines using Python and cloud platforms.
• Build feature engineering frameworks and reusable model components.
• Implement automated retraining, validation, monitoring, and reporting.
• Operationalize models via APIs and scalable services.
• Design AI-powered solutions with LLMs, RAG, semantic search, and agentic workflows.
• Develop prompt engineering strategies, evaluation frameworks, and governance.

Skills

Analytical thinking

Problem solving

Cross-functional collaboration

Stakeholder communication

Tools

LangChain

LangGraph

LangSmith

AutoGen

MCP/A2A architectures

Job description

Special Projects Group (SPG) is seeking an experienced AI/ML Data Scientist Contractor to design, build, and deploy advanced machine learning, predictive analytics, and AI-driven decision-support solutions.

This role will partner closely with business stakeholders, software engineers, product owners, and data teams to transform complex enterprise datasets into scalable forecasting, prediction, optimization, and intelligent automation capabilities.

The successful candidate will combine strong quantitative data science skills with practical experience delivering AI solutions into production environments. They will work across the full lifecycle of AI delivery, including problem definition, data engineering, model development, evaluation, deployment, monitoring, and continuous improvement.

This is a hands-on role requiring both technical depth and strong stakeholder engagement capabilities.

Responsibilities

Predictive Analytics & Forecasting

• Design, develop, and deploy predictive models to support business planning, forecasting, scenario modelling, and performance optimization.
• Develop machine learning solutions using structured, semi-structured, and unstructured enterprise datasets.
• Create statistical models that improve forecasting accuracy and support strategic decision making.
• Build explainable models and communicate key drivers, assumptions, risks, and confidence intervals.

Machine Learning Engineering

• Develop production-grade ML pipelines using Python and enterprise cloud platforms.
• Build feature engineering frameworks and reusable model components.
• Develop automated retraining, model validation, monitoring, and performance reporting capabilities.
• Partner with software engineering teams to operationalize models through APIs and scalable services.

Generative AI & Agentic Systems

• Design AI-powered solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), semantic search, and agentic workflows.
• Build intelligent assistants capable of reasoning over enterprise datasets and business processes.
• Develop prompt engineering strategies, evaluation frameworks, and model governance approaches.
• Leverage modern AI frameworks including LangChain, LangGraph, LangSmith, AutoGen, MCP/A2A-based architectures, or equivalent technologies.

Requirements

Good to Have

• Experience developing reusable application instrumentation or observability libraries.
• Experience with event-driven architectures and messaging platforms such as Kafka.
• Exposure to performance tuning, capacity planning, and reliability engineering practices.
• Experience participating in production support, incident management, and post-incident reviews.
• Familiarity with Infrastructure as Code and automated environment provisioning.
• Hands-on experience with Generative AI development tools such as GitHub Copilot, Cline, Claude Code, Cursor, or equivalent tools.
• Exposure to RAG, LLM-powered applications, or agentic AI systems.

Soft Skills

• Strong analytical, problem-solving, and debugging skills.
• Ability to work independently and take ownership.
• Clear communication and effective cross-functional collaboration.
• Strong focus on application reliability, maintainability, and operational excellence.
• Curiosity and willingness to learn evolving backend, cloud, and observability technologies.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.