Senior Applied AI Solutions Engineer – PHB Commercial Transformation

Overview

Senior, forward-deployed engineering role within the Strategy Deployment team of the Planetary Health Biosolutions (PHB) business division, designing, building, deploying and continuously improving AI-driven solutions that enhance commercial effectiveness.

What you'll do

• Partner with PHB commercial teams to understand complex workflows, business challenges, and user needs.
• Translate opportunities into practical AI solutions that create measurable business value.
• Design and build AI agents, applications, and workflows leveraging prompting, grounding, retrieval, tool use, actions, and orchestration.
• Develop and validate thin-slice solutions to assess user value and technical feasibility.
• Iterate rapidly based on user feedback and business outcomes.
• Lead multiple AI initiatives simultaneously, owning technical direction and delivery outcomes.
• Take on the assignments with the greatest ambiguity, integration complexity, enterprise risk or cross-functional scope, while helping establish reusable technical patterns and a high engineering and evaluation bar across the team.
• Define solution architectures for complex enterprise use cases and evaluate trade-offs across custom applications, Microsoft platforms, Salesforce capabilities, enterprise services, and third-party providers.
• Integrate AI solutions securely with enterprise platforms including Microsoft 365, Salesforce, and approved AI services.
• Build integrations using APIs, connectors, and workflow technologies while implementing appropriate identity, authorization, and approval controls.
• Develop solutions utilizing both structured and unstructured data, enterprise knowledge repositories, and retrieval-augmented generation (RAG) patterns.
• Ensure solutions are secure, scalable, maintainable, reusable, and aligned with responsible AI principles.
• Establish evaluation methodologies, quality standards, and release criteria for AI solutions.
• Design and execute functional, integration, regression, and AI-specific evaluations covering reliability, groundedness, retrieval quality, agent behavior, and user experience.
• Validate solutions with users and determine whether to scale, iterate, or discontinue initiatives based on evidence.
• Deploy, monitor, troubleshoot, and continuously improve production solutions.
• Document architectures, patterns, and learnings to support future reuse and scale across the organization.

What you'll need

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience.
• 4–8 years of relevant professional experience building and deploying AI, GenAI, or agent-based solutions in real-world environments.
• Strong hands-on experience with Large Language Models (LLMs), AI agents, prompting, grounding, retrieval-augmented generation (RAG), tool use, and orchestration techniques.
• Strong programming skills in Python and/or JavaScript/TypeScript.
• Experience with APIs, data integration, version control (Git), testing, and CI/CD practices.
• Experience building enterprise workflows and integrations using technologies such as Microsoft Power Platform, Power Automate, Azure Logic Apps, Salesforce Flow, REST APIs, or comparable solutions.
• Experience taking AI solutions from prototype to production, including testing, deployment, monitoring, and continuous improvement.
• Understanding of cloud platforms, identity and access management, secure data handling, responsible AI, and operational reliability.
• Strong stakeholder management and communication skills with the ability to explain technical concepts to diverse audiences.
• Excellent written and verbal English communication skills.

Nice to have

• Experience with Microsoft Copilot Studio, Microsoft Foundry, Salesforce Agentforce, UiPath, or similar enterprise AI platforms.
• Experience working with commercial, sales, marketing, or customer-facing business functions.
• Demonstrated ability to select appropriate technologies based on business outcomes rather than platform preference.
• Experience operating effectively in highly ambiguous and fast-changing environments.

Details

• Location: Bangalore.
• Application deadline: 23 November 2026.