Senior Applied AI/ML Engineer

Google LLC; Bengaluru; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Google LLC in Bengaluru, India is seeking an Applied AI/ML Engineer to lead end-to-end AI and agentic solutions within the Finance Data and AI (DnA) team. You will design, deploy, and scale multi-agent systems that transform legacy finance workflows into AI-native processes.

You will collaborate with product, engineering, and finance stakeholders to translate complex problems into concrete specifications, and ensure systems are auditable, reliable, and aligned with business goals.

Qualifications

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
• 8 years of experience in full-stack development for end-to-end machine learning solutions.
• Experience building Agentic tools and systems (production-ready, not POCs).
• Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows.
• Experience in classical ML modeling (e.g., time-series forecasting, tree-based models) alongside modern Large Language Model (LLM)/Generative AI tooling.
• Demonstrated expertise in developing and deploying AI or ML models and utilizing modern observability/monitoring tools to track performance, latency, and model drift.
• Excellent communication and storytelling skills, with an ability to translate complex technical architectures and probabilistic model behaviors to executive finance leadership.

Responsibilities

• Lead the technical design of multi-agent workflows, utilizing a various toolkit (ML and Gemini LLMs) to solve complex, multi-layered financial problems.
• Build, prototype, and scale end-to-end AI agents. Outline system architectures that prioritize reliability, usability, and auditability ensuring clear human-in-the-loop interfaces for finance professionals.
• Take prototypes from isolated testing environments to scaled production systems. Design and deploy high-availability model endpoints with health checks, error handling, retries, and fallback mechanisms.
• Implement evaluation frameworks and guardrails to eliminate logical errors, hallucinations, and biases in automated financial decision-making.
• Partner closely with Product Managers, Engineers, and Finance stakeholders to translate ambiguous finance problems into concrete technical specification. Act as a self-sustainingtechnical leader who helps unblock system integration hurdles in partnership with Engineering teams.

Skills

Analytical thinking

Communication

Education

Master's degree in quantitative discipline

Tools

Python

R

SQL

Job description

X In most instances, this position requires in-person interviews as part of the hiring process.

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  

Preferred qualifications:

• 8 years of experience in full-stack development for end-to-end machine learning solutions.
• Experience building Agentic tools and systems (production-ready, not POCs).
• Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows.
• Experience in classical ML modeling (e.g., time-series forecasting, tree-based models) alongside modern Large Language Model (LLM)/Generative AI tooling.
• Demonstrated expertise in developing and deploying AI or ML models and utilizing modern observability/monitoring tools to track performance, latency, and model drift.
• Excellent communication and storytelling skills, with an ability to translate complex technical architectures and probabilistic model behaviors to executive finance leadership.

About the job

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

As an Applied AI/ML Engineer, in Finance Data and AI (DnA) team, you will lead the technical strategy, design, and deployment of end-to-end AI/ML and agentic solutions to transform legacy finance processes into AI-native workflows. You will operate at the intersection of advanced machine learning and product-driven transformation. You will build models, design self-sustaining, self-correcting agentic systems that partner with finance Googlers to drive unprecedented efficiency across Google's finance organization.

Responsibilities

• Lead the technical design of multi-agent workflows, utilizing a various toolkit (ML and Gemini LLMs) to solve complex, multi-layered financial problems.
  
• Build, prototype, and scale end-to-end AI agents. Outline system architectures that prioritize reliability, usability, and auditability ensuring clear human-in-the-loop interfaces for finance professionals.
  
• Take prototypes from isolated testing environments to scaled production systems. Design and deploy high-availability model endpoints with health checks, error handling, retries, and fallback mechanisms.
  
• Implement evaluation frameworks and guardrails to eliminate logical errors, hallucinations, and biases in automated financial decision-making.
  
• Partner closely with Product Managers, Engineers, and Finance stakeholders to translate ambiguous finance problems into concrete technical specification. Act as a self-sustainingtechnical leader who helps unblock system integration hurdles in partnership with Engineering teams.
  

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.