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First American
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Senior AI Engineer-AI COE

Senior AI Engineer-AI COE

First American

3 - 7 years

20 - 25 Lacs

bengaluru

Posted:2 weeks ago| Platform:

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Skills Required

orchestration consulting agile back office workflow high performance computing microsoft monitoring software services python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Deliver measurable ROI in cost savings, efficiency gains, capacity increases, or revenue opportunities.
De-risk adoption by testing feasibility early and validating value continuously.
Build durable capability by leaving behind not only working solutions but also reusable assets and skilled teams.

Core principles of this team:

Embedded Collaboration: FDE squads work side-by-side with product teams, ensuring relevance and adoption.*
Hypothesis-Driven: Every case starts with a clear ROI hypothesis and defined success metrics.
Rapid Iteration: Quick prototypes vali assumptions in weeks, not months.
Time-Boxed: 8-10 week phases with explicit milestones create urgency and accountability.
Sustainable Handover: Co-building ensures product teams can own, extend, and scale solutions after FDEs disengage.

As part of this agile and mission-driven team, youll work on the front lines of AI transformation, applying cutting-edge foundation models to solve complex, real-world challenges from enhancing customer experiences to streamlining operations and uncovering new revenue opportunities.

We re looking for passionate individuals who thrive in fast-paced, collaborative environments, are committed to ethical AI practices, and are excited by the opportunity to help reshape a 135-year-old company from the inside out.

Role Summary: As an AI Engineer in our Centre of Excellence, you will be instrumental in building, deploying, and maintaining production-ready AI applications using readily available foundation models . You will bridge the gap between model development and practical application, ensuring robust, scalable, and efficient AI systems that deliver tangible value.

Key Responsibilities:

Design and implement end-to-end AI systems , integrating foundation models into various applications and workflows.
Apply and optimize model adaptation techniques , including prompt engineering , Retrieval-Augmented Generation (RAG), and finetuning, to tailor foundation models for specific use cases.
Develop and integrate AI architecture components such as context enhancement, input/output guardrails, model routers/gateways, caching mechanisms, and agent patterns to ensure system reliability and security.
Implement AI pipeline orchestration to define and chain together different components of an AI system, ensuring seamless data flow and complex workflow execution.
Optimize AI model inference for latency and cost, utilizing techniques like quantization, distillation, and parallelism, and demonstrate proficiency in working with GPUs and large compute clusters .
Collaborate closely with Data Scientists to integrate trained models and with Data Engineers to ensure efficient data pipelines for AI applications.
Contribute to defining and implementing systematic evaluation pipelines for AI applications, focusing on metrics such as factual consistency, generation capability, and instruction-following for open-ended outputs.
Engage in continuous monitoring and observability of AI systems in production to detect failures, drifts, and identify opportunities for improvement and cost savings.
Assist in productizing AI-powered outputs and features, ensuring alignment with customer needs and product strategy.

Required Skills & Qualifications:

Proven experience in building applications with foundation models and deploying AI systems into production environments.
Strong proficiency in prompt engineering, RAG, and finetuning techniques for model adaptation.
Familiarity with AI architecture patterns and their practical implementation.
Understanding of inference optimization techniques and experience with high-performance computing environments (e.g., GPUs).
Knowledge of AI evaluation methodologies for open-ended models and experience in setting up robust evaluation pipelines.
Proficiency in programming languages commonly used in AI development, such as Python , with an understanding of relevant APIs and frameworks.
Ability to work in an iterative, experimental environment and adapt to rapidly changing model capabilities and tools.
Excellent communication and collaboration skills for working with diverse, cross- Functional teams.

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Senior AI Engineer-AI COE