Job Title

AI/ML Lead – Lending Automation & GenAI Orchestration Role Type - Full-time, Hands-On AI/ML Leadership Work Location - Hyderabad About Us-BizAcuity Who 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 The Role We’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 Will Architect and implement AI features aligned to our lending workflows — starting with NLP, valuation automation, and orchestration Work hands-on to build prototypes, integrate APIs (OpenAI, Claude, AWS Comprehend, etc.), and ship production-ready features Guide our data team on what data needs to be captured and structured for optimal AI use Manage model lifecycles — from selection and integration to monitoring, fine-tuning, and retraining Orchestrate 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 rates Collaborate with the Engineering Lead to ensure AI components integrate smoothly with the Node/React platform Present AI concepts, prototypes, and outcomes to UK-based stakeholders in a clear, business-oriented way Keep up-to-date with AI trends and recommend new tools and techniques that can accelerate delivery or improve accuracy You Should Have 7–12 years of total experience, with at least 3 years hands-on in AI/ML development and architecture Proven track record integrating AI APIs and deploying GenAI-driven features into production Experience 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 rules Hands-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 decisions Experience with model lifecycle management — evaluation, bias checking, retraining Strong communication and presentation skills for non-technical stakeholders Experience working alongside software developers to embed AI features into a production web platform Bachelor’s or Master’s in Computer Science, AI/ML, or related field Bonus Experience in fintech or lending platforms Experience with vector databases, RAG (retrieval-augmented generation) patterns, and prompt engineering What Success Looks Like Three AI features shipped to production in 12 months 80%+ satisfaction rating from internal users and stakeholders AI features reduce manual work and improve process speed without quality drop Data team aligned on AI data readiness Stakeholders clearly see value in AI roadmap and outputs Initial Screening Criteria Essential Experience Years of experience: 7–12 in tech, 3+ in AI/ML hands-on Portfolio/examples: Deployed AI/NLP features in production (APIs + orchestration) Model lifecycle: Experience monitoring, improving, and retraining models API integration: Comfortable with multiple AI/ML API providers Communication: Evidence of clear technical-to-business translation Nice-to-Have Enhancers Fintech or lending platform experience Experience with valuation or document-heavy financial workflows Proven use of RAG, vector databases, or custom LLM tuning