AI/ML Architect

Job Description

• *Role/Position:** AI/ML Architect

• *Department:** Product Development

• *Industry Preference:** Product\-Based Organization

• *Experience:** 9\+ Years (Mandatory)

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

o Goal\-based reasoning

o Multi\-step decision\-making

o Tool/API orchestration

o Multi\-agent collaboration

 Design GenAI/LLM architectures using AWS Bedrock, Azure OpenAI, HuggingFace, LangChain,

and Transformer\-based models.

 Establish architectural patterns for

o Agent memory, context management, feedback loops

o Human\-in\-the\-loop decision governance

Safe autonomous execution AI\-Driven Cloud Enablement

 Architect solutions leveraging AWS Bedrock for GenAI\-powered

o Infrastructure optimization

o Predictive scaling

o 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

o Natural Language Processing (NLP) – clinical notes, claims text, coding,

summarization, chatbots

o Computer Vision – document ingestion, imaging, OCR

o Predictive analytics \& recommender systems – revenue forecasting, denial

prediction, patient engagement

o 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

o Spark, Hadoop, EMR, Redshift, BigQuery, Databricks, Kafka

 Design real\-time and batch pipelines feeding AI agents with

o Logs, metrics, events

o 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

o AWS (Bedrock, SageMaker, Lambda, EC2, EKS)

o Azure (OpenAI, Azure ML)

o GCP (AI Platform)

 Design microservices and API\-first architectures, leveraging .NET Core APIs as AI/agent

control planes.

 Establish deployment standards using

o Docker, Kubernetes

o Serverless architectures

 CI/CD and DevOps pipelines

AgentOps, MLOps \& Platform Governance

 Define AgentOps / MLOps frameworks covering

o Model, agent, prompt, and tool versioning

o Monitoring, observability, and drift detection

o 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

o Bots

o Scripts

o Cloud operations

Support hybrid automation where AI agents coordinate with human approvals

Security, Compliance \& Responsible AI

 Define AI governance and security architecture, ensuring

o HIPAA, GDPR, SOC 2 compliance

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

 Establish guardrails for

o Ethical AI

o Bias mitigation

o 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

o Claims processing

o Coding \& billing automation

o Denial prediction and management

o 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.

 Strong background in US Healthcare and RCM platforms.

 Hands\-on experience with multi\-agent systems, autonomous AI, and AI\-driven automation.

Pay: ₹3,000,000\.00 \- ₹4,000,000\.00 per year

Work Location: In person