AI/ML Lead

AI/ML Lead – Lending Automation & GenAI OrchestrationRole Type - Full-time, Hands-On AI/ML LeadershipWork Location - HyderabadAbout Us-BizAcuityWho are we? BizAcuity is on a mission to help enterprises get most out of their data by providing Business Intelligence and Data Analytics services, product development and consulting services for clients across globe in various domains / verticals.Established in 2011, by a strong leadership team and a team of 200+ engineers, we have made a mark as a world class service provider and compete with large service providers to win business. BizAcuity has developed and delivered high class enterprise solutions to many medium to large clients using modern and the best technologies in the data engineering and analytics world. Our services include - Business Intelligence Consulting , Advanced Analytics, Managed Services, Data Management, Cloud Services, Technology Consulting , Application Development and Product Engineering.For more information on BizAcuity, log on RoleWe’re looking for a hands-on AI/ML Lead who can design and deliver AI-powered solutions while guiding developers on how to integrate them into our core platform. Expect to spend roughly 50 % of your time writing and shipping code and 50 % shaping architecture, mentoring the team, and representing AI to stakeholders. You’ll work on NLP-driven document parsing, GenAI orchestration for lending workflows, and valuation automation. You’ll be comfortable integrating existing AI APIs, managing model lifecycles, and ensuring our data is AI-ready. You’ll report to the Engineering Lead and work closely with the data engineering team, product managers, and UK stakeholders.You WillArchitect and implement AI features aligned to our lending workflows — starting with NLP, valuation automation, and orchestrationWork hands-on to build prototypes, integrate APIs (OpenAI, Claude, AWS Comprehend, etc.), and ship production-ready featuresGuide our data team on what data needs to be captured and structured for optimal AI useManage model lifecycles — from selection and integration to monitoring, fine-tuning, and retrainingOrchestrate multi-step GenAI processes that interact with multiple PRD modules (e.g., Credit Committee Pack Builder, Comms parsing)Work with product to define KPIs, measure AI feature impact, and maintain high satisfaction ratesCollaborate with the Engineering Lead to ensure AI components integrate smoothly with the Node/React platformPresent AI concepts, prototypes, and outcomes to UK-based stakeholders in a clear, business-oriented wayKeep up-to-date with AI trends and recommend new tools and techniques that can accelerate delivery or improve accuracyYou Should Have7–12 years of total experience, with at least 3 years hands-on in AI/ML development and architectureProven track record integrating AI APIs and deploying GenAI-driven features into productionExperience with NLP workflows — document ingestion, entity extraction, summarisation, sentiment analysis, etc.Strong grasp of AI orchestration — building multi-step workflows combining APIs, prompts, and business rulesHands-on coding ability (Python strongly preferred for AI, familiarity with JS/TS for integration a plus)Understanding of data requirements for AI and ability to guide data teams on schema and storage decisionsExperience with model lifecycle management — evaluation, bias checking, retrainingStrong communication and presentation skills for non-technical stakeholdersExperience working alongside software developers to embed AI features into a production web platformBachelor’s or Master’s in Computer Science, AI/ML, or related fieldBonusExperience in fintech or lending platformsExperience with vector databases, RAG (retrieval-augmented generation) patterns, and prompt engineeringWhat Success Looks LikeThree AI features shipped to production in 12 months80%+ satisfaction rating from internal users and stakeholdersAI features reduce manual work and improve process speed without quality dropData team aligned on AI data readinessStakeholders clearly see value in AI roadmap and outputsInitial Screening CriteriaEssential ExperienceYears of experience: 7–12 in tech, 3+ in AI/ML hands-onPortfolio/examples: Deployed AI/NLP features in production (APIs + orchestration)Model lifecycle: Experience monitoring, improving, and retraining modelsAPI integration: Comfortable with multiple AI/ML API providersCommunication: Evidence of clear technical-to-business translationNice-to-Have EnhancersFintech or lending platform experienceExperience with valuation or document-heavy financial workflowsProven use of RAG, vector databases, or custom LLM tuning