Technical Architect - ML

• We are seeking an experienced MLOps/AIOps Architect who can drive end-to-end implementation of MLOps strategy and also contribute broadly across other enterprise AI/ML programs. This role demands a strong architectural mindset, hands-on technical depth, and the ability to design scalable, cloud-native machine learning operations across traditional ML and modern LLM workflows., * Architect and implement the MLOps strategy for the programme, ensuring alignment with the project proposal and delivery roadmap.
• Design and own enterprise-grade ML/LLM pipelines covering model training, validation, deployment, versioning, monitoring, and CI/CD automation.
• Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.).
• Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems.
• Serve as a technical authority across multiple internal and customer projects, contributing architectural patterns, best practices, and reusable frameworks.
• Enable observability, monitoring, drift detection, lineage tracking, and auditability across ML/LLM systems.
• Define and implement standards for model deployment, monitoring, governance, and automation to ensure production-grade reliability and scalability.
• Collaborate with cross-functional teams - data engineering, platform, DevOps, and client stakeholders - to deliver production-ready ML solutions.
• Ensure all solutions adhere to security, governance, and compliance expectations, particularly around handling cloud services, Kubernetes workloads, and MLOps tools.
• Conduct architecture reviews, troubleshoot complex ML system issues, and guide teams through implementation across cloud-native ML platforms.
• Mentor engineers and provide guidance on modern MLOps tools, platform capabilities, and best practices.

• The ideal candidate will bring experience with SageMaker-based MLOps pipelines, evaluation of equivalent tooling stacks, hybrid MLOps/LLMOps automation, CI/CD orchestration, governance, monitoring, automation and production-grade scalability patterns., * Expierence working in ML/AI engineering or MLOps roles with strong architecture exposure.
• Strong experience in leading enterprise grade MLOps strategy and its execution.
• Proven experience in implementing the adoption of enterprise-grade MLOps platforms with client data science teams.
• Proven leadership in defining and executing enterprise MLOps strategy.
• Demonstrated success in driving the adoption of enterprise-grade MLOps platforms with client data science teams.
• Strong expertise in AWS cloud-native ML stack, including: SageMaker(primary), EKS, Lambda, API Gateway, CI/CD (CodeBuild/CodePipeline or equivalent).
• Hands-on experience with at least one major MLOps toolset and awareness of alternatives: MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, Seldon. Deep understanding of model lifecycle management (feature engineering->training registry deployment
• monitoring).
• Experience implementing or supporting LLMOps pipelines, including: prompt versioning, evaluation metrics, automation frameworks.
• Deep understanding of ML lifecycle: data ingestion, feature engineering, training, evaluation, model packaging, CI/CD, drift detection, monitoring, and governance.
• Strong experience with AWS SageMaker (Pipelines, Feature Store, Model Registry, Model Monitor).
• Experience implementing ML CI/CD pipelines including automated training, testing, validation, model promotion, and endpoint deployment.
• Experience working on Infrastructure as Code (IaC) tools and CI/CD pipelines.
• Experience with Kubernetes based development.
• Experience with feature engineering pipelines and Feature Store management.
• Understanding of lineage tracking: training data snapshot, feature versions, code versioning, metadata tracking, reproducibility.
• Hands-on experience with AWS Bedrock and Agentcore service.
• Experience with CloudWatch, SageMaker Model Monitor, Prometheus/Grafana.
• Strong foundation in Python and cloud-native development patterns.
• Solid understanding of security best practices, IAM, secrets management, and artifact governance.

Other Qualifications (OQs):

• Experience with vector databases, RAG pipelines, or multi-agent AI systems.
• Exposure to DevOps and infrastructure-as-code (Terraform, Helm, CDK).
• Hands-on understanding of model drift detection, A/B testing, canary rollouts, and blue-green deployments.
• Familiarity with Observability stacks (Prometheus, Grafana, CloudWatch, OpenTelemetry).
• SQL and data transformation experience using Snowflake, Databricks, Spark.
• Ability to translate business goals into scalable AI/ML platform designs.
• Strong communication and cross-team collaboration skills.
• Ability to guide engineering teams through technical uncertainty and design choices.

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

About Quantiphi:

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies-we solve the problems that matter most to our clients.

Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries.

Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. #SolvingWhatMatters.

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:

• 21 Google Cloud Partner of the Year awards in the past 10 years
• 3 AWS AI/ML Partner of the Year awards
• 3 NVIDIA Partner of the Year awards
• 3 Snowflake Partner of the Year awards
• Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms

Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.

We are also proud to be certified as a Great Place to Work-reflecting our commitment to our people and our culture., * Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale.

• Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
• Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents.
• Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.