Project Role: AI Infrastructure ArchitectProject Role Description

Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost, and scalability of the computational stack. Advise on AI infrastructure technology and vendor evaluation, selection, and full stack integration.

Must Have Skills

- Databricks Unified Data Analytics Platform

Good to Have Skills

- AI Agents & Workflow Integration

Experience Requirement

- Minimum 15 years of experience is required

Educational Qualification

- 15 years full-time education

Role Summary / DescriptionAI Powered Tech Talent

As a Technical Architect in AI Infrastructure Architecture, you will act as a senior technical authority for Databricks-based AI/ML and lakehouse infrastructure, shaping the technical vision, reference architecture, standards, and implementation strategy for large-scale AI systems. You will evaluate complex choices across workspace architecture, compute clusters, model lifecycle, model serving, data/feature pipelines, governance, observability, security, and cost optimization while guiding senior and lead architects/Technical Architects to deliver resilient, scalable, and production-ready AI infrastructure. You will bring industry experience across enterprise AI adoption, compliance, reliability, FinOps, and platform modernization to help clients translate AI infrastructure trade-offs into measurable business value.

Key Responsibilities

- Set the overarching Databricks AI infrastructure vision, strategy, and reference architecture for large-scale AI/ML and lakehouse systems, including workspace architecture, compute, storage, orchestration, model serving, and observability.
- Own complex architectural decisions across Databricks workspaces, clusters/serverless compute, jobs, MLflow, Model Registry, Unity Catalog, Feature Technical Architecting, Delta Lake, and cloud integrations, rationalizing options against client standards and business objectives.
- Architect and prototype cost-optimized distributed training, feature Technical Architecting, and model-serving environments, building benchmarks, proof-of-concepts, and reusable implementation patterns.




- Define architecture standards, reusable infrastructure-as-code patterns, CI/CD approaches, ML pipeline deployment patterns, monitoring strategy, SLAs/SLOs, and cost/performance governance for production AI/ML systems.
- Lead architecture assessments and design reviews, validating findings through hands-on implementation, profiling, performance tuning, and troubleshooting across jobs, clusters, libraries, storage, security, and serving layers.
- Evaluate emerging Databricks, lakehouse, vector search, LLMOps, and model-serving capabilities, and recommend where they belong in enterprise solutions.
- Provide executive and client-level technical advisory, translating platform trade-offs into clear, defensible recommendations connected to business outcomes.
- Mentor architects and Technical Architects, build community best practices, and represent the practice in internal and external technical forums.

Required Qualifications

- Bachelor's degree in Computer Science, Computer Technical Architecting, Information Technology, or a related Technical Architecting field.
- Minimum 6 years of experience coding, building, monitoring, troubleshooting, designing, and operating AI/ML infrastructure, cloud platforms, data platforms, model deployment pipelines, or large-scale Technical Architecting solutions.
- Strong understanding of AI/ML concepts and the compute, infrastructure, orchestration, and deployment foundations required to run production AI systems.
- Minimum 6 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, PowerShell, or equivalent Technical Architecting languages.
- Experience with data pipeline and workflow management tools such as Apache Airflow, Kubeflow, managed orchestration services, or platform-native workflow tooling.
- Proven experience leading AI infrastructure projects and teams,



including technical direction, design reviews, delivery governance, and stakeholder alignment.
- Strong project management, communication, problem-solving, and cross-functional collaboration skills in quick-paced client or enterprise environments.
- Demonstrated experience evaluating and selecting AI technologies, frameworks, reference architectures, and platform services for production solutions.

Required Skills/Experience

- Expert-level hands-on architecture experience with Databricks workspaces, clusters/serverless compute, jobs, MLflow, Model Registry, Unity Catalog, Delta Lake, Feature Technical Architecting, and model-serving capabilities.
- Deep knowledge of Spark-based distributed processing, training/model pipelines, lakehouse architecture, model deployment, data governance, observability, and resilience Technical Architecting.
- Strong experience with Python, SQL, Spark, Terraform/Databricks Asset Bundles, Git-based CI/CD, security guardrails, monitoring, and platform cost optimization.
- Ability to evaluate multiple Databricks architecture options and produce standards, patterns, decision records, benchmarks, and executive-ready recommendations.
- Experience applying MLOps/DataOps/InfraOps practices for experiment tracking, model registry, deployment automation, monitoring, incident response, and rollback strategies.

Good to Have Skills

- Databricks certifications such as Databricks Machine Learning Professional, Data Technical Architect Professional, or related lakehouse architecture credentials.
- Industry experience designing lakehouse and AI infrastructure for BFSI, healthcare, retail/e-commerce, telecom, manufacturing, energy, or public sector environments with compliance, security, and reliability constraints.
- Exposure to LLMOps, vector search, retrieval pipelines, feature stores, GPU-backed model training, model optimization, and low-latency model serving.
- Experience with Unity Catalog governance, enterprise architecture roadmaps, vendor/partner management, FinOps, and production support operating models.

Locations

Job No. ATCI-5700992-S2061833 | Pune | Required Skill: Databricks Unified Data Analytics Platform

📌 AI Infrastructure Architect (Pune)
🏢 Accenture
📍 Pune