AI/ML Architect

Product Development Position Overview

We are seeking a highly experienced AI/ML Architect to define, design, and govern enterprise-scale AI/ML and Agentic AI platforms. This role is responsible for architecting GenAI/LLM-powered, autonomous, and cloud-native AI systems that operate across healthcare and Revenue Cycle Management (RCM) workflows.

The AI/ML Architect will provide technical leadership and architectural direction across intelligent agents, multi-agent orchestration, NLP, predictive analytics, Big Data platforms, cloud infrastructure, APIs, and RPA ensuring solutions are scalable, secure, compliant, explainable, and production-ready.

This is a hands-on architecture and strategy role, bridging business outcomes, engineering execution, and responsible AI governance.

Job Roles Responsibilities

AI/ML Agentic AI Architecture

- Define end-to-end AI/ML and Agentic AI architecture for enterprise platforms.
- Architect autonomous AI systems capable of:
- Goal-based reasoning

- Multi-step decision-making

- Tool/API orchestration

- Multi-agent collaboration

- Design GenAI/LLM architectures using AWS Bedrock, Azure OpenAI, HuggingFace, LangChain, and Transformer-based models.

- Establish architectural patterns for:
- Agent memory, context management, feedback loops

- Human-in-the-loop decision governance

Safe autonomous execution AI-Driven Cloud Enablement

- Architect solutions leveraging AWS Bedrock for GenAI-powered:
- Infrastructure optimization

- Predictive scaling

- Log intelligence and anomaly detection

Enable seamless integration of AI/ML models into application and infrastructure layers via APIs

GenAI, NLP Advanced AI Capabilities

- Architect AI solutions across:
- Natural Language Processing (NLP) clinical notes, claims text, coding, summarization, chatbots

- Computer Vision document ingestion, imaging, OCR

- Predictive analytics recommender systems revenue forecasting, denial prediction,



patient engagement

- Deep learning reinforcement learning

- Define standards for prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), and LLM lifecycle management.

Data, Big Data Intelligence Platforms

- Architect enterprise data and AI intelligence platforms using:
- Spark, Hadoop, EMR, Redshift, BigQuery, Databricks, Kafka

- Design real-time and batch pipelines feeding AI agents with:

- Logs, metrics, events

- Structured unstructured healthcare and RCM data

- Enable continuous learning pipelines and reinforcement loops for AI agents and models.

Cloud-Native Platform Architecture

- Define cloud-native AI architectures across:
- AWS Bedrock, SageMaker, Lambda, EC2, EKS

- Azure OpenAI, Azure ML

- GCP AI Platform

- Design microservices and API-first architectures, leveraging .NET Core APIs as AI/agent control planes.
- Establish deployment standards using:

- Docker
- Kubernetes

- Serverless architectures

- CI/CD and DevOps pipelines

AgentOps, MLOps Platform Governance

- Define AgentOps / MLOps frameworks covering:
- Model, agent, prompt, and tool versioning

- Monitoring, observability, and drift detection

- Safe rollout, rollback, and experimentation strategies

- Architect auditability and explainability into AI and agent workflows.

Ensure AI systems meet enterprise reliability, scalability, and resilience standards

Automation, RPA Orchestration

- Architect integration between AI agents and RPA platforms (UiPath, Automation Anywhere).
- Enable AI-driven orchestration of:
- Bots

- Scripts





- Cloud operations

Support hybrid automation where AI agents coordinate with human approvals

Security, Compliance Responsible AI

- Define AI governance and security architecture, ensuring:
- HIPAA, GDPR, SOC 2 compliance

- Secure model access, data isolation, and role-based controls

- Establish guardrails for:

- Ethical AI

- Bias mitigation

- Explainable and auditable decision-making

- Oversee secure deployment of AI models and agents in regulated healthcare environments.

US Healthcare RCM Domain Enablement :

- Architect AI solutions supporting:
- Claims processing

- Coding billing automation

- Denial prediction and management

- Payment posting and revenue forecasting

Ensure architectures align with US healthcare data standards, workflows, and compliance requirements

Leadership Strategic Influence :

- Act as the AI/ML architectural authority, guiding engineers, data scientists, and platform teams.
- Partner with product, cloud, security, and business leaders to align AI strategy with business outcomes.
- Mentor senior engineers and contribute to architecture reviews, reference designs, and best practices.
- Drive innovation through research, POCs, whitepapers, and AI thought leadership

Candidate Requirements

- Bachelor s or Master s degree in Computer Science, AI, Data Science, or related field.
- 8 12+ years of experience in AI/ML engineering, data platforms, and cloud architecture.
- 4+ years in AI/ML architecture or technical leadership roles.
- Proven experience designing GenAI, NLP, LLM-based, and Agentic AI systems.
- Robust background in US Healthcare and RCM platforms.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI/ML Architect (Maharashtra)
🏢 Credence Resource Management
📍 Maharashtra