Technical Architect Ai Ml in India

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for people who have a strong background in data science and cloud architecture to join our AI/ML Workload Services team to create exciting new offerings and capabilities for our customers! This team within the Services Delivery group will be working with customers using Snowflake to expand their use of the Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be highly technical and hands-on, where you will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators. AS A TECHNICAL ARCHITECT, AI/ML AT SNOWFLAKE, YOU WILL: Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements Work hands-on where needed using SQL, Python, and APIs to build POCs that demonstrate implementation techniques and best practices on Snowflake technology for GenAI and ML workloads Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own Maintain deep understand

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for people who have a strong background in data science and cloud architecture to join our Professional Services team to help create exciting new offerings and capabilities for our customers! This team will be working with customers using Snowflake to expand their use of the Snowflake Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be more strategic, advising our clients on best practices and advice to implement Data Science workloads on Snowflake. You will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators, while maintaining oversight and direction to ensure successful outcomes AS A TECHNICAL ARCHITECT - AI/ML AT SNOWFLAKE, YOU WILL : Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements Work hands-on where needed using SQL, Python, to build POCs that demonstrate implementation techniques and best practices on Snowflake tech

Want to be a bswifter? At bswift we’ve been transforming benefits administration since 1996, making it simpler, smarter, and more human. Our state-of-the-art, cloud-based technology and services empower employees to understand, manage, and love their benefits. From downtown Chicago, and remotely across the country, we serve thousands of companies and millions of people nationwide, reducing administrative burdens and freeing HR teams to focus on creating thriving, people-first workplaces. We’re looking for motivated and goal-driven individuals who share our passion for delivering excellence and creating solutions that make a difference. The reward is a fun, flexible and creative environment with ample opportunity for professional and personal growth. If you love the bswift values of pursue excellence, embrace accountability, deliver superior service, and be a great place to work, we want to hear from you! About the Role We are looking for an AI Engineer II to design, build, and deploy cutting-edge generative AI applications , including agentic workflows and intelligent chat experiences , that transform how employees interact with their benefits. This role goes beyond individual contribution—you will own complex AI features end-to-end , influence architecture decisions around LLMs and agent systems , and mentor junior engineers . You will play a key role in bringing secure, scalable, and high-performance AI solutions to production using AWS cloud technologies. You will collaborate closely with software engineers, architects, product managers, and cross-functional teams to deliver seamless and impactful user experiences Key Responsibilities 1. Solution Design & Development Lead the design and development of scalable, secure, and high-performance applications . Architect robust backend systems and integrate them with frontend applications and third-party services. Drive technical decisions and participate in design reviews alongside senio

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Principal Data Cloud Architect - SI Partners We are seeking a highly experienced and results-driven AI/ML focused Principal Data Cloud Architect to join our Partner Solution Engineering (PSE) team. Our mission is to empower System Integrator (SI) partners to rapidly achieve technical wins and successful production deployments of AI/ML solutions on the Snowflake AI Data Cloud. Snowflake, the AI Data Cloud, enables teams to seamlessly run analytical workflows, develop agentic apps, and train models using both structured and unstructured data. With over 4,000 customers leveraging our gen AI and ML technology weekly, we are at the forefront of AI innovation. This role is crucial in accelerating AI/ML customer journey technical wins and production deployments being implemented by SI partners. IN THIS ROLE YOU WILL PERFORM: Strategic Account Alignment with top accounts for SI partners (Focus on Acceleration): Unlock High-Impact Customer Journeys: Identify and prioritize AI/ML customer journeys for SI partner top accounts, focusing on quick wins and high consumption, informed by your understanding of SI partner needs. Expedited POCs and RFPs: Provide support for partners during RFI/RFP processes and POCs, ensuring rapid turnaround and successful outcomes, informed by your SI propo

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role We are currently seeking a Staff Software Engineer, Infrastructure to join the AI Platform team that powers seamless insights and interaction through natural language and data intelligence across our AI products. As a Staff Software Engineer, you’ll architect, build, and operate the backend and platform systems that power AI Platform. You’ll work across service design, distributed systems, cloud infrastructure, event-driven processing, observability, CI/CD, and production reliability, helping shape the technical direction of a platform that supports scalable, client-facing AI experiences. This role requires a strong software engineering foundation combined with deep infrastructure and systems thinking. We are looking for an engineer who can write high-quality production code, make sound architectural tradeoffs, and own platform capabilities end-to-end — not someone focused only on scripting, cloud configuration, or infrastructure tooling in isolation. You will collaborate closely with frontend, product, and AI/ML engineers to deliver reliable, secure, and scalable systems that align with Addepar’s standards of performance, resilience, and trust. Applicants must have legal authorization to work in the country where this role is based o

Title: Senior AI QA Engineer Location: Bengaluru (Bangalore) Opportunity: As a Senior AI QA Engineer for our Precision Patient Care Pipeline , you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies . Key Responsibilities: Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations. Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics). Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity. Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation. Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics. Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior. Requirements: 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation. Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems. AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, an

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA

Position Overview: We are looking for a Senior Software Engineer to drive technical excellence, architect complex systems, and elevate our engineering team. You will own critical technical decisions, lead major initiatives from conception to delivery, and set the standard for engineering quality across our products. As a senior engineer, you will architect and lead the development of sophisticated AI-enabled features and infrastructure. This includes designing MCP server architectures, building advanced RAG systems, implementing agentic AI workflows, and establishing patterns that scale across our product portfolio. You will combine deep technical expertise in both traditional software engineering and AI/ML to deliver production-grade solutions. What You'll Do Lead the design and implementation of AI integration infrastructure (MCP servers, orchestration layers, API gateways) Build sophisticated AI features including advanced RAG systems, agentic workflows, and multi-step reasoning Establish AI engineering best practices, security patterns, and quality standards Lead technical initiatives from requirements through production deployment Make critical architectural decisions balancing performance, scalability, cost, and maintainability Design AI evaluation frameworks and implement quality benchmarks Debug and resolve complex production issues across traditional and AI systems Required Qualifications Tech Stack Core: Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, Docker AI & Integration: Python, MCP, AWS Bedrock, LangGraph/Semantic Kernel, Vector Databases, RAG Core Technical Skills 5+ years professional development with proven track record of delivering complex systems Strong Node.js and JavaScript/TypeScript expertise Advanced React and frontend architecture skills Extensive AWS architecture experience Expert PostgreSQL database design, optimization, and performance tuning Deep understanding of microservices, distributed systems, and

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. Responsibilities Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization. Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges. Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations. Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR). Implement parsing, semantic analysis, and IR generation for deep learning frameworks. Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers. Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations. Qual

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. What You’ll Do: Architect the Future of AI Infrastructure: You will design, build, and own the end-to-end platform that supports the entire lifecycle of our ML models—from massive-scale distributed training to ultra-low-latency, highly-available inference. Optimize and Serve Cutting-Edge Models: You'll implement and scale sophisticated inference stacks for LLMs using frameworks like vLLM, TensorRT-LLM, or SGLang . You’ll solve complex challenges in throughput, latency, token streaming, and automated scaling to deliver a seamless user experience. Empower AI Innovation: You will act as a strategic partner to our AI Research and Data Science teams. You’ll create a seamless developer experience that accelerates their ability to experiment, fine-tune, and deploy groundbreaking models with velocity and confidence. Automate Everything: You'll develop robust CI/CD/CT (Continuous Training) pipelines using tools like Argo Workflows, ArgoCD, and GitHub Actions to automate model validation, deployment, and lifecycle management, ensuring our systems are both agile and rock-solid. What are we looking for Experience: 5+ years in infrastructure or software engineering, with at least 2+ years laser-focused on MLOps or ML infrastructu

Role: DataOps Solution Architect — Azure Data Platform (Fabric & Databricks) Owns end-to-end architecture of the Azure data platform (Fabric, Databricks, Azure services) and sets the governance, security, and DataOps standards engineering teams implement. Design authority and primary architecture advisor to the client, not the day-to-day builder. Experience Required 8-10+ years overall in data engineering / cloud architecture, including 3+ years as a Solution Architect or in a comparable design-authority role. Microsoft Fabric: 2+ years hands-on. Azure Databricks: 4+ years hands-on. Proven track record designing and delivering enterprise-scale Azure data platforms end-to-end. Azure is mandatory ; experience across multiple client engagements or a consulting/SI background is a plus. Core Technical Expertise Azure Platform Fabric & Databricks architecture. ADF. ADLS. Entra ID. Key Vault. Monitor/Log Analytics. Microsoft Fabric Workspace & environment strategy. Lakehouse/Warehouse. OneLake. Pipelines/Notebooks. REST APIs/CLI. Governance. Azure Databricks Workspace strategy. Unity Catalog. RBAC. Jobs/Workflows. Delta Lake. Asset Bundles. ML platform integration. DevOps & IaC Azure DevOps/GitHub CI/CD. Terraform & Bicep. Branching/release strategy. Reusable IaC modules. Security & Networking Entra ID. RBAC architecture. Private Endpoints/DNS. Key Vault integration. DataOps Standards CI/CD & test gates for pipelines. Data-quality frameworks. Observability/alerting architecture. SLAs/SLOs. Incident-management practices. FinOps guardrails. Key Responsibilities Own end-to-end architecture; translate requirements into scalable, secure, cost-effective designs. Design enterprise-scale Fabric/Databricks architecture including workspace, networking, security, and governance. Set standards for CI/CD, IaC, DataOps, and environment management; ensure enterprise security and regulatory compliance. Evaluate technology options; identify architectural risks a

SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter , LinkedIn , Facebook and Instagram . Job Title: Distinguished Engineer - Data Architect Role Overview: We are looking for a Distinguished Engineer- Data Architect to design and build the data foundation for our AI-driven security platform. In this role, you will own the architectural blueprint and core implementation of our data strategy, transforming massive streams of high-velocity network traffic logs, customer configurations, and security alerts into high-performance, ML-ready data fabrics. As part of a lean, elite three-person Data & AI team, you will serve as the ultimate technical authority on data scale, streaming architecture, multi-tenant security, and cost-efficient storage systems. Key Responsibilities: Architect the Core Data Platform: Design, implement, and evolve a unified blueprint for streaming and batch data processing capable of ingesting, normalizing, and storing petabyte-scale, high-velocity security telemetry. Enable AI & Advanced Analytics: Partner directly with the Lead AI Engineer to architect the underlying storage, retrieval systems, and feature stores—including optimal vector database structures and data la

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is looking for a Sr. Principal Data Scientist to set the technical direction for the ML models and AI sub-agents that drive growth, monetization, efficiency, and retention across the customer lifecycle. You’ll architect the systems, define the modeling and evaluation standards, and shape the roadmap for how Smartsheet uses applied ML and agentic AI to serve millions of customers. The data is unusually rich: petabyte-scale execution data spanning two decades of how real work gets done. You are a recognized technical leader who moves fluidly between architecture, prototype, and production; raises the bar for the data scientists around you; and partners with senior product and engineering leaders to make decisions that compound across the org. You will work primarily with Product and Engineering and will be a part of Smartsheet’s Business Intelligence team. This full-time position reports to the Director of Data Science and is based in Smartsheet’s Bengaluru, India office. You Will: Set the technical direction for how Smartsheet uses applied ML and agentic AI across the customer lifecycle — what gets built, what doesn’t, and what good looks like Architect the systems behind the sub-agents: how they ground themselves in evidence, how risk and confidence are calibrated, how decisions are evaluated, and how all of it stays safe and trustworthy at scale Define the modeling, evaluation, and experimentation standards the team follows — from offline metrics to online rollout to production monitoring Personally ship the