Technical Architect- Machine Learning

Role:                                 Architect Machine Learning

Experience Level:           8+ Years

Work location:                Bangalore, Mumbai

What youll do:

As a Technical Architect (TA) in the Healthcare & Life Sciences (HCLS) unit at Quantiphi, you will be a senior technical leader responsible for governing the quality, design, and strategic direction of our most critical AI initiatives. This is a highly visible, client-facing architectural role where you will spend 25% to 50% of your time on hands-on prototyping, writing code for complex scenarios, and guiding the engineering team through technical uncertainty.

You will design enterprise-grade, highly scalable, and secure AI/ML platforms that span Generative AI, Agentic systems, traditional ML, and Computer Vision. You will act as the primary technical advisor for strategic client accounts, collaborating with VPs, CTOs, and Chief AI Officers. You will establish practice-wide architectural standards, lead pre-sales solutioning and proposals, and mentor Associate Architects and senior engineers to drive technical excellence at scale.

Role & Responsibilities:

• Enterprise AI Architecture: Design and govern large-scale, mission-critical AI platforms meeting 99.99%+ availability, security, scalability, and compliance requirements in the healthcare and life sciences domain.
• Client Leadership & Solution Pitching: Act as the primary technical contact for strategic accounts. Lead pre-sales efforts, design high-impact solutions, write technical proposals, and pitch them to stakeholders.
• Hands-on Prototyping & Escalation: Maintain active hands-on involvement (25% to 50% of time). Build multi-agentic prototypes, design core frameworks, and step in to write production code or debug complex system issues when the team faces blockers.
• Generative AI & Agentic Platform Design: Architect enterprise-grade agentic systems, multi-agent platforms, autonomous workflow orchestrations, and advanced memory/context management systems leveraging the Model Context Protocol (Server, Client, Gateway).
• Standards & Practice Governance: Establish comprehensive LLMOps and MLOps standards (including prompt versioning, automated evaluation, CI/CD, drift detection, and production monitoring). Define reference architectures and reusable frameworks to accelerate project delivery.
• AI Security & Compliance: Design AI security architectures for regulated industries, ensuring strict compliance with HIPAA, HITRUST, GDPR, SOC 2, and OWASP LLM Top 10 security requirements.
• Mentorship & Practice Growth: Mentor Associate Technical Architects, senior engineers, and delivery teams. Conduct architectural reviews and manage technical debt across engagements.

Skills expectation:

• Must have:

• Experience: 8+ years of progressive experience in AI/ML engineering, with at least 3+ years in a technical leadership or architectural role.

• Enterprise Architecture & System Design:

• Deep expertise in system integration, legacy modernization, cloud-native design, and API gateway architectures.

• Proven ability to visually represent complex, multi-system architectures and explain technical trade-offs with deep, structured reasoning.

• Advanced ML & Deep Learning Foundations:

• Mastery of statistical ML, deep learning base architectures (Transformers, CNNs, RNNs), and Computer Vision platforms.

• Proficiency in Python and frameworks such as PyTorch or TensorFlow.

• Generative AI & Agentic Platform Architecture:

• Deep understanding of the entire agent development lifecycle, multi-agent system design, and A2A (Agent-to-Agent) communication protocols.

• Hands-on experience with Agentic AI frameworks (e.g., LangGraph, CrewAI, AutoGen, LlamaIndex, LangChain).

• Proven experience with Model Context Protocol (MCP), prompt engineering strategies (Chain of Thought, Tree of Thoughts), and LLM optimization (PEFT, SFT, QLoRA, DPO).

• Practical implementation of Vector Databases (e.g., Pinecone, Milvus, Qdrant, OpenSearch).

• Robust MLOps & LLMOps:

• Experience designing end-to-end ML lifecycles (data ingestion, feature store, registry, deployment, monitoring, drift detection).

• Strong SQL and data transformation experience using BigQuery, Snowflake, Databricks, or Spark.

• AI Security & Regulatory Compliance:

• Proven experience designing compliant architectures under HIPAA, HITRUST, SOC 2, or GDPR.

• Good to have:

• HCLS Domain Expertise: Deep domain knowledge of Healthcare & Life Sciences (clinical systems, digital diagnosis, software as a medical product).

• Cloud Expertise: Professional Cloud Architect and Machine Learning Engineer certifications on AWS or GCP.

• Thought Leadership: Publications, technical blogs, or conference presentations in Agentic/Generative AI or Enterprise Architecture.

Behavioural skills:

• Technical Reasoning & Probing: Exceptional ability to justify architectural choices, explain complex technical decisions under deep probing, and evaluate alternative tooling stacks.
• Stakeholder Presence: Exceptional presentation and communication skills. Proven ability to pitch proposals, influence decision-makers, and build strong relationships with key stakeholders.
• Willingness to Walk the Talk: A hands-on leader who leads by example, stepping in to write code, build prototypes, and guide engineers through technical uncertainty.
• Strategic Mentorship: Passion for coaching Associate Architects and senior engineers, establishing standards, and fostering a culture of technical excellence.

What is in it for you:

• Shape Enterprise AI Strategy: Guide the AI/ML strategy for strategic healthcare enterprises through your architectural decisions.
• Tackle Complex Challenges: Design novel solutions that push the boundaries of Agentic AI while navigating real-world constraints.
• Practice-Wide Impact: Establish the technical standards, reference architectures, and reusable frameworks that guide hundreds of engineers.
• Key Stakeholder Advisory: Build trusted advisor relationships with healthcare key stakeholders, guiding critical technology transformations.