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.
AI/ML & Agentic AI Architecture
- Define end-to-end AI/ML and Agentic AI architecture for enterprise platforms.
- Architect autonomous AI systems capable of:
- Multi-step decision-making
- 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
- 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:
- 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)
- Design microservices and API-first architectures, leveraging .NET Core APIs as AI/agent control planes.
- Establish deployment standards using:
- 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:
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:
- 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:
- 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
- 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.
Technical Expertise:
- Agentic AI, autonomous systems, multi-agent orchestration
- GenAI & LLM stacks: Transformers, HuggingFace, LangChain, RAG, fine-tuning, prompt engineering
- AI/ML frameworks: TensorFlow, PyTorch, Keras, scikit-learn
- Big Data & Streaming: Spark, Hadoop, EMR, Redshift, BigQuery, Databricks, Kafka
- Cloud platforms: AWS, Azure, GCP (AI/ML services)
- APIs & microservices: .NET Core, REST, event-driven architectures
- RPA & automation platforms
- DevOps, CI/CD, Kubernetes, Docker
- AI governance, security, and compliance frameworks.
Skillset:
- Strong architectural and systems-thinking mindset
- Ability to translate complex AI concepts into business-aligned solutions
- Executive-level communication and stakeholder engagement
- Leadership, mentorship, and influence across large teams
- Passion for autonomous AI platforms and healthcare transformation
Strategic Impact:
- Establish enterprise AI/ML and Agentic AI platforms
- Enable autonomous, self-healing, and intelligent cloud operations
- Position AI agents as first-class platform components
- Drive scalable, compliant, and responsible GenAI adoption in healthcare & RCM
Kindly Note: At Credence, we uphold the highest standards of integrity in our recruitment process. We do not charge any fees at any stage of the hiring process, and we strictly prohibit any third parties, vendors, or individuals from soliciting money in exchange for job opportunities at Credence.
If you are approached by anyone requesting payment or offering you a position at Credence in exchange for money, do not engage with them. Such actions are fraudulent and not authorized by Credence. Please report any such incidents immediately to our official HR team at [email protected]
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