AI/ML Lead Lending Automation & GenAI Orchestration

Role Type : Full-time | Hands-On AI/ML Leadership

Work Location : Hyderabad

About BizAcuity :

BizAcuity empowers enterprises to maximize the value of their data through Business Intelligence, Advanced Analytics, AI/ML-driven automation, and Product Engineering. Since our inception in 2011, we have served global clients across fintech, retail, hospitality, gaming, and healthcare sectors, delivering high-quality, scalable, and secure data-driven solutions.

Our expertise spans Data Engineering, Cloud Services, AI/ML Consulting, Technology Consulting, Application Development, and Managed Services. With a team of 200+ skilled engineers and a culture of innovation, we combine modern technologies with deep business insight to build enterprise-grade solutions that compete with the biggest names in the industry.

Learn more : https ://bizacuity.com

Role Overview :

We are seeking a hands-on AI/ML Lead who will design, develop, and deploy AI-driven lending automation solutions with a focus on NLP workflows, GenAI orchestration, and valuation process automation. This is a 50% coding and delivery role, 50% architecture and leadership role. You will work directly with our Engineering Lead, Data Engineering Team, Product Managers, and UK-based stakeholders to define, architect, and integrate AI capabilities seamlessly into our Node.js + React enterprise platform.

Key Responsibilities :

AI Solution Architecture & Development :

- Architect and implement end-to-end AI/ML features aligned with lending workflows :

1. NLP Document Parsing OCR, entity extraction, semantic search, summarization, classification.

2. Valuation Automation Predictive modeling for asset and loan valuations.

3. GenAI Orchestration Multi-step, multi-service automation workflows.

- Develop production-grade AI services in Python, integrating with REST/GraphQL APIs, microservices, and event-driven architectures.

- Integrate GenAI APIs (OpenAI GPT, Anthropic Claude, AWS Comprehend, Google Vertex AI, etc.) into existing systems.

Model Lifecycle Management :

- Select, train, fine-tune, and deploy models (LLMs, transformer-based models, classical ML).

- Implement model monitoring pipelines for accuracy, drift detection, bias evaluation, and retraining triggers.

- Optimize inference latency, throughput, and scalability for production workloads.

Data Readiness & Governance :

- Collaborate with Data Engineering to ensure AI-ready data pipelines (schema design, storage format, vectorization strategies).

- Establish data labeling, augmentation, and versioning processes for supervised and semi-supervised learning.

- Ensure compliance with data privacy regulations (GDPR, RBI guidelines) and ethical AI principles.

AI Workflow Orchestration :

- Design and implement multi-step AI orchestration layers combining LLM prompts, RAG (Retrieval-Augmented Generation), and business rules.

- Build custom prompt chains and tools to handle complex workflows like Credit Committee Pack creation and communication parsing.

Stakeholder Collaboration & Leadership :

- Translate complex AI concepts into clear business benefits for non-technical stakeholders.

- Mentor and guide developers on AI integration best practices.

- Track AI feature KPIs and demonstrate measurable business impact.

Required Skills & Experience :

- Total Experience : 7 - 12 years in software engineering, with 3+ years hands-on AI/ML solution delivery.

- Proven record of deploying AI/NLP features in production environments.

- Proficiency in Python (FastAPI, Flask, LangChain, Hugging Face Transformers, PyTorch/TensorFlow).

- Strong experience with NLP pipelines tokenization, embeddings, semantic search, summarization, classification, sentiment analysis.

- Expertise in AI orchestration frameworks (LangChain, Haystack, LlamaIndex) and workflow automation.

- Proficient in REST API design, microservices, and integrating AI with JavaScript/TypeScript-based backends.

- Deep understanding of data structures, feature engineering, and vector databases (Pinecone, Weaviate, FAISS).

- Solid grasp of MLOps tools (MLflow, Kubeflow, AWS SageMaker, Azure ML).

- Familiarity with cloud-native AI deployments (AWS, Azure, GCP).

- Strong communication skills for technical-to-business translation.

Bonus Skills :

- Fintech or lending automation platform experience.

- Familiarity with financial document workflows (KYC, underwriting, valuation reports).

- Hands-on experience with RAG pipelines, prompt engineering, and custom LLM training.