About the team

Roku pioneered streaming to the TV and continues to innovate and lead the industry. While we are well-positioned to help shape the future of television – including TV advertising – around the world, continued success relies on its investment in our machine learning capabilities. Roku offers millions of options to our users: movies, episodes, news, sports, and channels from all around the world. The Roku Content Platform is key to onboarding content into the Roku ecosystem, delighting our customers. Building a content knowledge platform that provides insights to downstream systems like Search, Recommendations, Ads, and Voice to shape customers' experiences is why we’re actively looking for a Senior Machine Learning / AI Engineer, Content Platform who can drive further innovation.

About the role

Roku pioneered streaming to the TV and continues to innovate and lead the industry. While we are well-positioned to help shape the future of television – including TV advertising – around the world, continued success relies on its investment in our machine learning capabilities.

Roku offers millions of options to our users: movies, shows, news, sports, and channels from all around the world. The Roku Content Platform is key to onboarding content into the Roku ecosystem, delighting our customers. Building a content knowledge platform that provides insights to downstream systems like Search, Recommendations, Ads, and Voice to shape customers' experiences is why we’re actively looking for a Senior Machine Learning / AI Engineering Manager who can drive further innovation.

The person in this role will leverage their technical skills, business intuition, and analytical thinking to build best-in-class machine learning products. This includes integrating Generative AI capabilities and Vision Models to enrich content quality and user engagement. This is a role for a hardened ML practitioner and a highly skilled organizational leader. You will be the architectural and operational bridge between deep AI research and fast-paced product delivery. If you know how to build a 3-year vision for content discovery and translate it into 2-week shipping cycles, this is your team.

What you’ll be doing

• Vision & Strategy: Define the roadmap for ML within the Content Platform..
• Technical Leadership: Provide high-level guidance on model architecture and MLOps infrastructure to ensure models are scalable and production-ready.
• People Management: Lead and grow a high-performing team of ML Engineers. You will be responsible for career development, performance management, and maintaining a culture of rigorous experimentation.
• Cross-Functional Execution: Partner with Product, Engineering, and Content Strategy to align ML initiatives with business goals.
• Delivery: Champion a culture of incremental delivery. Balance long-term R&D with the need to deliver measurable improvements to the production environment.

We’re excited if you have

• 10+ years of total experience in software/ML engineering, with at least 5 years in a dedicated people management leadership role.
• MS or BS in Computer Science, Mathematics, or a related quantitative field.
• You possess a deep theoretical and practical understanding of Machine Learning. 
• You understand the business of streaming and how ML directly impacts the bottom line.
• You can explain complex model to a non-technical executive just as easily as you can debate architecture with a seasoned engineer.
• Proven track record of deploying large-scale ML models into production environments.
• Experience with modern ML stacks (e.g., LLMs, PyTorch, TensorFlow, Spark, and cloud-native MLOps tools).

Job Title: GenAI Developer/ Engineer

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Location - Bangalore

Experience - 6 to 10

Skills and Qualifications:

Preferred skills:

Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)

GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel

Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities:

• Develop scalable Python applications focused on GenAI
• Knowledge of Snowflake Cortex is a big plus.
• Learn and apply techniques like document chunking and embeddings
• Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Follow coding best practices and contribute to testing and documentation
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 12–15+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

• Documentation and teaching: you make complex systems understandable; you uplevel teams. 

 Please complete the attached Internal Transfer Request Form and submit.   

Please make sure to apply with your Coupang e-mail address.   

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview 

The Taiwan Data, Analytics & AI team is the engine driving Coupang’s rapid expansion in the Taiwan market. Our mission is to transform massive datasets into actionable intelligence and automated systems that power business decisions. As we scale, we are transitioning from foundational growth to a sophisticated enterprise AI ecosystem. We are building the next generation of data services that ensure every stakeholder across the Taiwan organization has access to high-integrity, automated, and intelligent insights.

As a Staff Machine Learning Engineer, you will be a technical leader responsible for the architecture and automation of our regional data intelligence layer. Your primary focus will be bridging the gap between raw data and organizational knowledge. You will lead the automation of our Knowledge Base, govern the integrity of our core metrics, and scale our analytics services to support the entire Taiwan organization.

This is a high-impact role where technology meet business, and you will design systems that not only provide data but ensure that the "truth" behind the data is refreshed, accurate, and easily accessible through AI-driven interfaces and help us become true AI first Analytics Organisation.

What You Will Do

• Automated Knowledge Engineering: Design and implement end-to-end ML pipelines to automate the creation and maintenance of a centralized Knowledge Base, utilizing LLMs and RAG (Retrieval-Augmented Generation) to synthesize complex business logic.

• Metric Integrity & Governance: Develop systemic checks and automated validation frameworks to ensure the integrity of business metrics. You will be the architect of a "Single Source of Truth," ensuring definitions remain consistent across all AI and reporting services.

• AI-Driven Pipeline Automation: Architect "Self-Healing" data pipelines using AI tools to automate schema mapping, error detection, and recovery. Implement LLM-powered agents to generate, optimize, and document ETL code, reducing manual engineering overhead.

• Scalable AI Services: Architect and scale existing Data and Analytics services to handle the increasing demands of the entire Taiwan organization, ensuring high availability and low-latency access to insights.

• Feedback & Refresh Loops: Build automated feedback mechanisms to identify "stale" content or drifting metric definitions. You will design the workflows that ensure both new and existing knowledge content is refreshed regularly based on user behavior and data shifts.

• Systemic Optimization: Drive innovation in semantic retrieval and query understanding to allow non-technical stakeholders to interact with complex data layers using natural language.

• Enablement & Training: Act as a force multiplier by enabling and training various reporting functions (Finance, Ops, Marketing). You will create the tools and frameworks that allow these teams to self-serve with high confidence.

• Technical Mentorship: Lead by example in code quality, system design, and experimentation. Mentor senior and mid-level engineers, fostering a culture of technical excellence and continuous improvement.

Basic Qualifications

•  Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field.

• 8+ years of professional experience in software engineering and applied machine learning (with at least 2 years in a Staff or Lead capacity).

• Proficiency in Python or Java, with deep experience building production-grade ML systems and scalable data pipelines.

• Strong experience with SQL and big data technologies (e.g., Spark, Presto/Trino, Airflow).

Preferred Qualifications

• Advanced Degree: Master’s or PhD in a relevant technical field.

• AI/LLM Expertise: Proven track record of deploying Large Language Models (LLMs), vector databases, and embedding-based retrieval systems in a production environment.

• Automated Management: Experience with AI-powered data management tools (e.g., automated data profiling, AI-driven data catalogs, or LLM-assisted SQL generation).

• Enterprise Scaling: Experience transitioning data organizations from "growth-phase" scripts to "enterprise-phase" robust microservices.

• Cloud Proficiency: Hands-on experience with AWS or GCP (SageMaker, Vertex AI, BigQuery).

• MLOps Mastery: Experience with ML lifecycle tools like MLflow, Kubeflow, or Weights & Biases to manage model lineage and data drift.

• Communication: Exceptional ability to communicate technical roadmaps to non-technical business leaders and influence cross-functional stakeholders in a fast-paced, global environment.

Type of work model 

• Hybrid 

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview 

The Taiwan Data, Analytics & AI team is the engine driving Coupang’s rapid expansion in the Taiwan market. Our mission is to transform massive datasets into actionable intelligence and automated systems that power business decisions. As we scale, we are transitioning from foundational growth to a sophisticated enterprise AI ecosystem. We are building the next generation of data services that ensure every stakeholder across the Taiwan organization has access to high-integrity, automated, and intelligent insights.

As a Staff Machine Learning Engineer, you will be a technical leader responsible for the architecture and automation of our regional data intelligence layer. Your primary focus will be bridging the gap between raw data and organizational knowledge. You will lead the automation of our Knowledge Base, govern the integrity of our core metrics, and scale our analytics services to support the entire Taiwan organization.

This is a high-impact role where technology meet business, and you will design systems that not only provide data but ensure that the "truth" behind the data is refreshed, accurate, and easily accessible through AI-driven interfaces and help us become true AI first Analytics Organisation.

What You Will Do

• Automated Knowledge Engineering: Design and implement end-to-end ML pipelines to automate the creation and maintenance of a centralized Knowledge Base, utilizing LLMs and RAG (Retrieval-Augmented Generation) to synthesize complex business logic.

• Metric Integrity & Governance: Develop systemic checks and automated validation frameworks to ensure the integrity of business metrics. You will be the architect of a "Single Source of Truth," ensuring definitions remain consistent across all AI and reporting services.

• AI-Driven Pipeline Automation: Architect "Self-Healing" data pipelines using AI tools to automate schema mapping, error detection, and recovery. Implement LLM-powered agents to generate, optimize, and document ETL code, reducing manual engineering overhead.

• Scalable AI Services: Architect and scale existing Data and Analytics services to handle the increasing demands of the entire Taiwan organization, ensuring high availability and low-latency access to insights.

• Feedback & Refresh Loops: Build automated feedback mechanisms to identify "stale" content or drifting metric definitions. You will design the workflows that ensure both new and existing knowledge content is refreshed regularly based on user behavior and data shifts.

• Systemic Optimization: Drive innovation in semantic retrieval and query understanding to allow non-technical stakeholders to interact with complex data layers using natural language.

• Enablement & Training: Act as a force multiplier by enabling and training various reporting functions (Finance, Ops, Marketing). You will create the tools and frameworks that allow these teams to self-serve with high confidence.

• Technical Mentorship: Lead by example in code quality, system design, and experimentation. Mentor senior and mid-level engineers, fostering a culture of technical excellence and continuous improvement.

Basic Qualifications

•  Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field.

• 8+ years of professional experience in software engineering and applied machine learning (with at least 2 years in a Staff or Lead capacity).

• Proficiency in Python or Java, with deep experience building production-grade ML systems and scalable data pipelines.

• Strong experience with SQL and big data technologies (e.g., Spark, Presto/Trino, Airflow).

Preferred Qualifications

• Advanced Degree: Master’s or PhD in a relevant technical field.

• AI/LLM Expertise: Proven track record of deploying Large Language Models (LLMs), vector databases, and embedding-based retrieval systems in a production environment.

• Automated Management: Experience with AI-powered data management tools (e.g., automated data profiling, AI-driven data catalogs, or LLM-assisted SQL generation).

• Enterprise Scaling: Experience transitioning data organizations from "growth-phase" scripts to "enterprise-phase" robust microservices.

• Cloud Proficiency: Hands-on experience with AWS or GCP (SageMaker, Vertex AI, BigQuery).

• MLOps Mastery: Experience with ML lifecycle tools like MLflow, Kubeflow, or Weights & Biases to manage model lineage and data drift.

• Communication: Exceptional ability to communicate technical roadmaps to non-technical business leaders and influence cross-functional stakeholders in a fast-paced, global environment.

Type of work model 

• Hybrid 

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

About the role:

As a Sr. Manager, Platform & Architecture you will lead the definition, governance & continuous evolution of the enterprise data architecture vision and roadmap, ensuring strong alignment with business strategy and digital transformation goals. This role is accountable for establishing modern, secure, and scalable data platform architectures that enable advanced analytics, AI/ML, generative AI, and self service data capabilities across the organization.

You will provide strategic leadership in embedding AI into the enterprise data platform, enabling use cases such as predictive analytics, intelligent automation, and generative AI, while ensuring responsible AI practices, model governance, data quality, and regulatory compliance.

The role requires deep expertise in data architecture, cloud data platforms, analytics ecosystems, and platform security, combined with strong people and stakeholder management skills. You will guide the evaluation and adoption of emerging technologies, oversee PoC initiatives, and drive the operationalization of AI/ML and GenAI solutions.

Working closely with data engineering, analytics, AI/ML, security, and business leaders, you will ensure the delivery of trusted, high performing, and future ready data and AI platforms that scale with organizational needs.

What you'll do:

Strategic Leadership & Architecture Vision

• Define and own the enterprise data architecture vision and roadmap aligned with business strategy.
• Establish architectural principles, standards, and best practices across data modeling, integration, metadata, and analytics
• Guide architectural decisions to support scalability, performance, security, and future growth.
• Evaluate and approve new data technologies, platforms, and tools

Team Management & Development

• Lead, mentor, and manage data modelers & architects, platform engineers and data engineers
• Set goals, conduct performance reviews, and support career growth and skills development
• Ensure effective workload planning, prioritization, and resource allocation
• Promote a culture of collaboration, documentation, and architectural discipline

Data Platform & Architecture Design

• Design and oversee end to end data architectures, including ingestion, storage, processing, analytics, and consumption layers
• Define scalable patterns for batch, near real time, and streaming data processing
• Establish standards for data platforms, ingestion frameworks, transformation and modeling approaches, and BI/visualization tools
• Ensure platform reliability, performance, scalability, and cost optimization

Platform Engineering, Security & Governance

• Architect platforms with security by design, including IAM, RBAC, data encryption, masking, and auditing
• Collaborate with security and compliance teams to meet regulatory and data privacy requirements
• Define and enforce data governance standards, including metadata management, lineage, data quality, and observability
• Support platform monitoring, availability, and operational excellence

Advanced Analytics & Innovation

• Enable advanced analytics use cases, including forecasting, predictive modeling, and statistical analysis
• Support data science and analytics teams by designing architectures for ML pipelines, feature stores, and model deployment
• Lead Proof of Concept (PoC) initiatives to evaluate new data, analytics, and platform tools
• Assess emerging technologies for scalability, security, integration, and business value

Self-Service & Data Enablement

• Drive the self-service analytics strategy to empower analysts and business users
• Design curated, governed data layers and semantic models for trusted self-service access
• Reduce dependency on IT by enabling reusable data assets and standardized analytics frameworks
• Partner with stakeholders to align data products with business needs

Experience you'll need:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field
• 10 - 15+ years of experience in data engineering, analytics, or platform architecture roles
• Strong experience designing and implementing modern data architectures and cloud data platforms.
• Hands-on and architectural experience with:
  • Snowflake or similar cloud data warehouse/data lake experience
  • Tableau or similar BI tools
  • Fivetran or equivalent ingestion tools
  • dbt or similar data transformation frameworks
• Proficiency in SQL, Python, Spark, and data modeling techniques.
• Experience with cloud platforms such as AWS, Azure, or GCP

Preferred Qualifications:

• Experience with advanced analytics, forecasting, and predictive modeling.
• Knowledge of ML/AI platforms and MLOps concepts.
• Strong understanding of data security, governance, and compliance frameworks.
• Excellent communication and stakeholder management skills.
• Experience working in large-scale or enterprise Data & Analytics environments.

Company Overview

At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.

What You’ll Be Doing

As a Lead ML Engineer in the Data Science team, you will work closely with the engineering, product, and operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality. 

In this role, you will find innovative ways to apply emerging technologies to improve business processes and drive more value for customers. The ideal candidate will have a strong background in machine learning model development, natural language processing and understanding, and data analysis which they can utilize to manage and improve our company’s AI/ML initiatives. 

• Architect and Own multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
• Build tools and capabilities that help with data ingestion to feature engineering, data management and organization
• Build tools and capabilities for scalability through distributed optimization 
• Deploy  cutting edge algorithms like LLMs etc. on GPUs at scale
• Work with stakeholders on the research and software engineering side of the company to understand how to support their teams
• Build tools and capabilities for model management and model performance monitoring
• Build operating services at scale with high availability and reliability
• Propose and implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
• Contribute and influence the ML infrastructure roadmap in collaboration with Data Science team

What we are looking for -

• Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 5+ years of experience in solving of experience in machine learning engineering problems 
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience with machine learning operations, software engineering, and architecture
• Experience with large-scale systems including parallel computing and GPUs
• Experience architecting and building an AI pipelines that supports productionization of ML models
• Experience with MLOps systems
• Strong programming skills in a scientific computing language such as Python, SQL
• Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
• Experience working with ML tools such as Tensorflow, Keras, and Pytorch
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Why you will love to work with us -

We have multiple brands, which are among the biggest brands operating on amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.

• Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models
• Deploy code using the most sophisticated tech stack like AWS, GCP etc.
• You will own projects end to end i.e., from exploration to final production
• You will be empowered to make decisions. It implies more responsibilities but high learning
• Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
• Forget endless meetings. Get things done and start making an impact from day 1
• Work hard, have amazing fun, create history, build the future of eCommerce 
• Start-up environment with a strong culture and values to accelerate your career 

Our values

Impact: Cogniters strive to make an impact in all that they do. We are result-oriented, always asking ourselves.

Ownership: Cogniters embrace a culture of ownership. We go beyond our comfort zones to contribute to the greater good, fostering inclusivity and sharing responsibilities for challenges and success. 

Relentless: Cogniters are relentless in their pursuit of innovation. We are determined and deliverable (never ruthless or reckless), facing challenges head-on and viewing setbacks as opportunities for growth. 

Introduction

We are seeking a dynamic and experienced Strategic Technical Advisor to spearhead the growth and operational excellence of our dedicated technical delivery and enablement function focused exclusively on our strategic customer. Crucially, this Hub operates as a key component of the larger Strategic Program organization dedicated to this customer.

This is a foundational role in a high-potential environment, as the Hub team will grow from an initial 6 technical resources to approximately 20 by the end of the year.

The successful candidate will be responsible for three critical outcomes:

1. Hub Build-Out: Hiring the team,  establishing the operational frameworks, best practices, and culture necessary to scale successfully and ensuring seamless integration with the strategic customer's priorities and the Strategic Program's goals.
2. Delivery Excellence: Guaranteeing the high-quality, successful, and impactful delivery of technical solutions, customer support and enablement programs for the customer.
3. Ecosystem Enablement: Developing and mentoring a 3rd party partner team to ensure they can independently support and extend the customer's platform usage.

The role requires a strong dual focus: Team Leadership and Technical Oversight. As the entire team consists of specialized technical resources—specifically Data Scientists, Data Engineers, and Solution Architects—and includes an integrated, dedicated Support function, the Hub Lead must act as a mentor and technical guide. They will be expected to direct and coach these technical experts on how to "show up" with professionalism and technical authority in complex, high-stakes customer-facing engagements.

Key Responsibilities

1. Technical Mentorship & Partner Enablement

2. Program Collaboration & Cross-Functional Coordination

3. Delivery Excellence & Customer Success

• Standards Implementation: Establish and enforce adherence to defined technical delivery standards and best practices on all projects, specifically tailored to meet the customer’s technical environment and compliance requirements.
• Escalation Management: Execute the internal escalation process for critical customer issues, ensuring timely resolution and coordinated communication with customer and support teams.
• Customer Feedback and Improvement: Analyze customer feedback and system performance data to propose and implement actionable improvements to engineering methodologies, developer tools, or team workflows. 

4. Financial and Operational Performance

•  Estimations & Scope Creep: Work with Program Managers to maintain accurate technical effort forecasts. Proactively flagging technical scope creep or resource bottlenecks.
•  

5. Talent Acquisition and Development

• Recruitment and Onboarding: Lead the deep-dive technical interview and selection process for all Hub candidates. Ensure every new hire raises the collective technical bar of the team.. Own and manage the complete onboarding process for new team hires.
• Engagement & Retention: Drive employee engagement for this dedicated team through regular check-ins and activities, using proactive measures to address retention risks.
• Training Strategy Execution: Develop and execute comprehensive training and upskilling plans that focus on both deep technical skills and customer-specific domain knowledge, leveraging standard Academy content while ensuring the Dedicated Support team is current on the customer's architecture and configuration.
• Knowledge Sharing Facilitation: Actively facilitate collaborative team work sessions to encourage knowledge sharing and capture team-developed process improvements or technical solutions to share with the broader organization.
• External Partner Quality: Track and report on the effectiveness and quality of the 3rd party partner staff to ensure skill and knowledge levels meet delivery and performance standards.

Key Performance Indicators (KPIs)

The Strategic Customer Hub Lead is accountable for monitoring and reporting on the following key metrics:

• Partner Readiness: Achieve [Metric/Level] in partner certification and readiness tracking.
• Customer Enablement : Track customer and partner completion rates for Academy coursework and Community engagement levels.
• Talent Retention & Engagement: Achieve and maintain a voluntary attrition rate below [Z]%.

Qualifications

• Technical Domain Expertise: Minimum of 15+ years of professional experience in a technical discipline relevant to the team (e.g., Data Engineering, Cloud Architecture, or Data Science/MLOps) ideally in a SaaS environment. Must have at least 5 years of experience in a role that required reviewing architecture and challenging technical decisions made by senior engineering staff. 
• Strategic Account Experience: Proven history of successfully leading technical delivery for a singular, large strategic customer or within a dedicated account structure. Demonstrated ability to navigate complex enterprise IT landscapes and align internal technical roadmaps with client-side architectural constraints.
• Architectural Governance & Program Alignment: Ability to operate effectively within a matrixed Strategic Program, serving as the "technical conscience" of the Hub to ensure all deliveries align with the broader program's long-term technical objectives. Experience providing technical direction to dotted-line support resources is essential.
• Partner & Learning Enablement: Demonstrated ability to mentor, train, or enable a 3rd party partner and to effectively leverage or develop formal learning pathways (Academy/training) for customer success.
• Team Building & Mentorship: Extensive experience in mentoring and coaching highly skilled technical professionals, specifically within an Indian delivery center context.
• Communication & Presence: Exceptional verbal and written communication skills necessary to articulate technical strategy to executive-level clients and effectively train team members on professional presence (the "how to show up" factor).

 Join the global Cognite community! 🌐

• Join an organization of 70 different nationalities 🌐 with Diversity, Equality and Inclusion (DEI) in focus 🤝
• ITPL office location (Bengaluru)
• A highly modern and fun working environment with sublime culture across the organization, follow us on Instagram @cognitedata 📷 to know more
• Flat structure with direct access to decision-makers, with minimal amount of bureaucracy
• Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries
• Join our HUB 🗣️ to be part of the conversation directly with Cogniters and our partners.
• Hybrid work environment globally

Why choose Cognite? 🏆 🚀

Join us in making a real and lasting impact in one of the most exciting and fastest-growing new software companies in the world. We have repeatedly demonstrated that digital transformation, when anchored on strong DataOps, drives business value and sustainability for clients and allows front-line workers, as well as domain experts, to make better decisions every single day. We were recognized as one of CNBC's top global enterprise technology startups powering digital transformation! And just recently, Frost & Sullivan named Cognite a Technology Innovation Leader! 🥇

 

 

 

Learn more about us

 

 

 

• Impact 2025
• Cognite's Industrial AI: Moonshot
• We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

 

 

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

Who We Are:
Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai. 

About the Role – Senior Member of Technical Staff – Software Development

Our SaaS platform serves enterprise customers with a reliable, secure, and scalable product built on modern microservices, event-driven data pipelines, and AI-powered capabilities.We are seeking a Senior Member of Technical Staff (Sr MTS) – Software Development to join our SaaS Platform team. This role is ideal for a backend engineer who has moved beyond writing individual features and is ready to take meaningful ownership of platform components, contribute to technical design, and start influencing the direction of the team. You will work alongside Staff and Principal Engineers on building microservices, data pipelines, and AI-integrated backend systems on AWS — developing both your technical depth and your ability to lead within a team.

Position Responsibilities: 

Feature Development & Ownership

• Take end-to-end ownership of backend features and services — from requirements and design through implementation, testing, deployment, and monitoring.
• Design and implement production-grade microservices in Golang, following team standards for gRPC and RESTful API patterns.
• Contribute meaningfully to technical design discussions; author design documents for features and components you own, incorporating feedback from senior engineers.
• Write well-tested, maintainable code; champion testing practices including unit, integration, and end-to-end tests within your feature area.
• Participate in on-call rotations; debug and resolve issues in distributed backend services and contribute to post-incident reviews.

Data Pipelines & AI Integration

• Build and extend data pipeline components that process, enrich, and route platform telemetry and events using AWS streaming and batch services (Kinesis, MSK, Glue, Step Functions).
• Integrate AI and LLM capabilities into backend services and pipeline stages — including model inference calls, output parsing, and result handling — under the guidance of Staff Engineers.
• Implement agentic AI workflow components such as tool-use handlers, retrieval-augmented generation (RAG) steps, and prompt orchestration layers as part of broader pipeline designs.
• Contribute to the reliability and correctness of AI pipeline components through thorough testing, output validation, and adherence to team guardrail standards.

Platform Reliability & Operations

• Ensure backend services you build are observable from day one: structured logging, metrics, distributed tracing, and alerting are treated as part of the definition of done.
• Apply AWS networking and security best practices in the services you build: secure IAM roles, VPC-aware service communication, and encryption in transit and at rest.
• Proactively identify and address reliability gaps, performance bottlenecks, and technical debt in platform components you own.
• Support deployment of services on AWS using team CI/CD pipelines and infrastructure-as-code tooling.

Collaboration & Team Contribution

• Collaborate effectively with Staff and Principal Engineers, product managers, and peers across a geographically distributed team.
• Conduct thorough code reviews and provide constructive, actionable feedback; help MTS engineers grow through mentorship on your area of expertise.
• Document APIs, service behavior, data flows, and runbooks clearly so teammates can understand, operate, and evolve your work.
• Participate actively in planning, estimation, and sprint ceremonies; raise technical risks and dependencies early.

Requirements

Experience & Education

• 3+ years of professional software engineering experience in backend development.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• Solid foundation in computer science fundamentals: data structures, algorithms, and operating systems.
• Demonstrated experience owning and shipping backend features or services in a production cloud environment.
• Experience working in collaborative, agile engineering teams; comfortable operating in fast-paced, high-growth environments.

Backend & Microservices

• Proficiency in Golang or a comparable strongly typed backend language; willingness to work primarily in Golang.
• Working understanding of microservices architecture: service boundaries, inter-service communication via REST and gRPC, and the trade-offs of distributed systems.
• Experience designing and implementing APIs with attention to correctness, reliability, and ease of use by other services.
• Familiarity with event-driven patterns and messaging systems such as Kafka, Kinesis, or SQS/SNS.
• Strong testing practices: unit, integration, and contract testing for backend services.

Agentic AI & LLM Integration

• Working knowledge of large language models (LLMs) and how they are integrated into backend systems via API calls (e.g., Amazon Bedrock, OpenAI, or Anthropic APIs).
• Familiarity with agentic AI concepts: tool use, multi-step reasoning, and agent orchestration frameworks such as LangChain, LlamaIndex, or Amazon Bedrock Agents.
• Ability to implement prompt templates, manage context windows, and handle model outputs reliably within backend service logic.
• Understanding of retrieval-augmented generation (RAG) patterns: embedding generation, vector store queries, and context injection into prompts.
• Awareness of production considerations for AI components: output validation, error handling, latency management, and cost awareness.

Data Pipelines

• Practical experience building or contributing to data pipelines for real-time or batch processing workloads.
• Familiarity with AWS data pipeline services: Amazon Kinesis, AWS Glue, Amazon MSK (Kafka), AWS Step Functions, or Amazon EMR.
• Understanding of how to embed AI/ML model inference calls as processing steps within a data pipeline.
• Ability to add pipeline observability: tracking throughput, latency, error rates, and data quality metrics.

AWS & Cloud Infrastructure

• Hands-on experience deploying and operating backend services on AWS; familiarity with core services including EC2, ECS/EKS, S3, RDS, and SQS/SNS.
• Basic understanding of AWS networking and security: VPC, security groups, IAM roles and policies, and encrypted communications.
• Experience with containerization (Docker) and deploying services in container-based environments.
• Comfort working with CI/CD pipelines, Git-based workflows, and infrastructure-as-code tooling (Terraform or AWS CDK is a plus).

Nice to Have

• Experience with Kubernetes (EKS) for container orchestration.
• Hands-on use of Amazon Bedrock or equivalent managed AI platforms for LLM inference.
• Experience with vector databases or embedding stores (OpenSearch, pgvector, Pinecone).
• Exposure to AWS managed data services such as Amazon Redshift, DynamoDB, or Aurora.
• Background in network security, cloud networking, or multi-cloud environments.
• Interest in or exposure to ML model lifecycle management and MLOps practices.

Interpersonal & Communication

• Clear written and verbal communication; able to write design documents, articulate technical decisions, and give constructive code review feedback.
• Collaborative team player who works well in cross-functional, geographically distributed teams.
• A growth mindset — eager to deepen expertise, take on new challenges, and mentor peers as you develop.

About the Opportunity

The Impact you bring to Cognite

Key Responsibilities

• Take product requirements and independently design, train, test, and deploy ML models (e.g., NLP, Vision-Language Models) for document parsing, layout analysis, and entity matching.
• Write high-quality, scalable production code (Python). Wrap your ML models into robust RESTful or gRPC APIs and integrate them seamlessly into existing industrial master data systems and workflows.
• Implement and maintain CI/CD pipelines for your models. Navigate complex deployment environments, manage containerized applications (Docker/Kubernetes), and optimize inference bottlenecks.
• Work with Principal engineers to translate high-level system architectures into concrete, scalable data pipelines and production-ready microservices.
• Design automated testing for ML pipelines. Monitor deployed models in production for data drift, latency, and accuracy, proactively implementing retraining strategies.
• Collaborate effectively with product managers to define ML capabilities. Provide code reviews and informal technical mentorship to engineers.

Required Skills and Qualifications

• Bachelor’s or Master's degree in Computer Science, Data Science, Software Engineering, or a related field.
• 6–10 years of industry experience in software engineering with a strong focus on machine learning, MLOps, and API development.
• Strong programming skills in Python with experience using backend web frameworks (e.g., FastAPI, Flask, Django) to serve models.
• Solid expertise in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
• Hands-on experience with containerization (Docker, Kubernetes), Linux environments, CI/CD tools (GitHub Actions, Jenkins), and deploying models on cloud platforms (AWS, Azure, or GCP).
• Solid understanding of software architecture, data structures, and algorithms to ensure performant code.
• Hands-on experience with distributed data processing frameworks (e.g., Apache Spark, Ray, Dask) and orchestrating complex data workflows (e.g., Apache Airflow, Dagster, Prefect).

What Sets your Role Apart

• Independently define the technical ML/SWE approach for ambiguous feature requests and deliver to production.
• Recognize the model is a small part of the solution; expertly manage aspects like API rate limiting, asynchronous processing, and robust data routing around ML components.
• Possess hands-on experience maintaining production ML models and designing resilient systems against poor data quality..

Preferred Qualifications

• Proven experience fine-tuning and deploying multimodal models for visual data and engineering diagrams in live environments.
• Built robust, production-grade RAG pipelines, expertly utilizing Vector/Graph Databases for high-accuracy entity retrieval.
• Familiar with orchestrating multi-step reasoning using frameworks like LangGraph or AutoGen for real-world problem-solving.
• Strong understanding of advanced OCR, layout parsing, and techniques for consistent structured JSON extraction from complex industrial PDFs. Manufacturing/OT dataset experience preferred.
• Ability to optimize LLMs/VLMs for inference latency (quantization, TensorRT, vLLM), potentially in constrained, on-premises environments.
• Experience with modern data lake/lakehouse architectures (Delta Lake, Iceberg, Databricks) for efficient querying and preprocessing of petabyte-scale unstructured data for LLM/VLM training and RAG.

 

 

 

Learn more about us

 

 

 

• Impact 2025
• Cognite's Industrial AI: Moonshot
• We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

 

 

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

Staff Data Scientist – Supply Chain AI (Small Language Models)  

At Avathon, we build AI products that solve real industrial problems at scale. We believe the future of enterprise AI lies in small, focused, high-performance models—deeply grounded in domain context—not just large, generic systems. 

We’re looking for an experienced Data Scientist to join our Supply Chain AI team in India. In this role, you’ll design, fine-tune, and deploy optimized Small Language Models (SLMs) that power production-grade AI features across logistics, planning, inventory, and demand forecasting. 

What Makes This Role Unique 

This is a product-first data science role. You won’t just build models—you’ll own how they show up in real products used by large enterprises. Your work becomes the intelligence layer that sits on top of our graph and indexing systems and directly drives customer outcomes. 

What You’ll Do 

• Build and fine-tune SLMs/LLMs for production use cases such as semantic search, forecasting, contract intelligence, and conversational insights. Optimize models for performance, cost, and latency using PEFT, quantization, and efficient inference techniques 

• Embed supply chain knowledge into models by working closely with domain experts and product teams 

• Enable agentic workflows, allowing AI Assistants to execute planning, optimization, and decision-support tasks 

• Integrate models into products using custom Lambdas, and a Graph-based microservices architecture  

• Apply vector search and semantic reasoning to help customers navigate complex supply chain relationships 

• Work with real enterprise data—ERP, logistics, inventory, supplier, and contract datasets 

• Deploy and operate models using strong MLOps practices on platforms like AWS, GCP or AZURE 

• Measure and improve quality, reducing hallucinations and improving reliability through continuous evaluation 
• Partner with engineering, product, and operations teams to ship impactful AI features end-to-end 

What We’re Looking For 

• Experience working with SLMs (Mistral, Phi, Nemotron, Llama variants), applying parameter-efficient fine-tuning (LoRA/QLoRA) to optimize task-specific natural language query answering with high accuracy and minimized hallucinations. 

• Strong understanding of supply chain data and workflows (logistics, inventory, procurement, ERP systems) 

• Familiarity with Knowledge Graphs and graph-based data modeling, including designing and querying Neo4j graphs for relationship-driven insights. 

• Solid hands-on skills in Python, PyTorch/TensorFlow, GraphQL, and vector databases 

• 8+ years of experience in forecasting, optimization, supply chain analytics, or AI-driven products 

• Experience designing Retrieval-Augmented Generation pipelines using document chunking, metadata filtering, hybrid (dense + sparse) retrieval, and SLM/LLM grounding for enterprise knowledge search. 

• Hands-on experience building and tuning FAISS-based vector indexes (IVF, HNSW, PQ) for large-scale semantic similarity search with low-latency production deployment 

• Experience taking models from prototype to production 

• Bonus: reinforcement learning, MARL, graph neural networks, or probabilistic modeling 

• Clear communication skills and a strong sense of product ownership 

Why Avathon 

You’ll work on core AI products, not experiments—solving complex supply chain problems for global enterprises, while building from India as a key innovation hub. 

If you enjoy shipping AI that delivers measurable business value, this role is for you. 

The Role

We are looking for an elite engineer who builds like a hacker and communicates like a consultant. You will not just be building models in a notebook; you will be deployed to the front lines to build, architect, and ship end-to-end Agentic AI products directly for our most strategic customers.

This is a high-stakes role. You will face "tricky" customers who have vague requirements and high expectations. Your job is to translate their chaos into technical order, write production-grade code, and deploy autonomous agents that solve their actual business problems.

What You Will Do

• Build & Deploy (60%):

Design and ship full-stack AI applications. You own the pipeline from data ingestion to the LLM inference layer to the frontend interface.

Architect autonomous agentic workflows (using frameworks like LangChain, LangGraph, or custom implementations) that can reason, plan, and execute complex tasks.

Write robust, clean, and highly testable code (Python/Typescript). "It works on my machine" is not acceptable; it must work in the customer's restricted cloud environment.

Handle DevOps and MLOps constraints: Dockerizing agents, managing Kubernetes clusters, and optimizing inference latency.

• Customer Engineering (40%):

Serve as the technical face of the company for our most demanding accounts.

Navigate complex stakeholder environments. You will push back on unrealistic demands, clarify ambiguous requirements, and steer "tricky" customers toward technically feasible solutions without breaking rapport.

Translate technical constraints into business value for non-technical executives.

Generate high-quality data for our customers and ability to review the data generated by other experts. This is one of the most critical aspects of the role.

The "Must-Haves"

• Experience: 8–12 years of total engineering experience. You started as a strong Software Engineer and evolved into an AI specialist.
• Education: B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution (IIT, MIT, Stanford, Harvard, Berkeley, CMU, or similar global top-ranking universities).
• Deep AI Fluency: You aren't just calling APIs. You understand RAG implementation nuances, vector database optimization, fine-tuning (LoRA/PEFT), and the architecture of agentic loops.
• Production Engineering: Experience with end-to-end deployment (AWS/GCP/Azure, CI/CD pipelines, Terraform, Docker).

The "Why You" (Soft Skills)

• Thick Skin & High EQ: You don't get flustered when a customer changes their mind for the third time in a week. You can hold your ground with a CTO and explain "why not" to a CEO.
• Extreme Attention to Detail: You catch the edge cases that others miss. You obsess over error handling, retry logic in agents, and data privacy.
• Grit: You enjoy the "messy" work of integrating legacy enterprise data just as much as prompting the latest model.

What will set you apart

• Public Code: A visible GitHub footprint is very helpful. We want to see your side projects, your contributions to open source, or your experiments with LLMs. Please include your GitHub link in your application.

Tech Stack

• Languages: Python (Expert).
• AI/Data (Expertise in all is not required): PyTorch, LangChain, LlamaIndex, Pinecone/Weaviate, OpenAI/Anthropic APIs, HuggingFace.
• Infra (Expertise in all is not required): Kubernetes, Terraform, AWS/GCP.

Solutions Architect

Role Overview 

As Solutions Architect you operate at the intersection of deep technical leadership and high-stakes client engagement. You will: 

• Own solution architecture and technical delivery for marquee customers, ensuring JazzX’s AGI platform unlocks measurable business value. 
• Guide multi-disciplinary squads (product, research, engineering, and customer success) from discovery through full production rollout. 
• Shape platform roadmap with field feedback, driving features that accelerate time-to-value and differentiate JazzX in the market. 

You are equally comfortable white-boarding LLM retrieval strategies, optimising prompt chains, troubleshooting Kubernetes deployments, or presenting to a C-suite audience. 

Key Responsibilities 

Qualifications 

Must-Have 

• 10–12 years of software engineering experience, 5+ in staff/principal or solution-architect roles. 
• Proven record delivering large-scale, low-latency distributed systems (Python, Java, Go, or C++). 
• Hands-on with LLM / AI frameworks (LangChain, LlamaIndex, PyTorch, TensorFlow) and productionising ML pipelines. 
• Expertise integrating REST/GraphQL APIs, streaming platforms (Kafka), SQL & NoSQL stores, and vector DBs. 
• Outstanding client-facing communication, executive-level presentation, and stakeholder-management skills. 

Nice-to-Have 

• Masters or PhD in AI/Data Science/Computer Science 
• Experience shipping RAG or agent-based AI systems in regulated industries. 
• Nice to have certifications in cloud architecture, data engineering, or security (e.g., AWS SA-Pro, CKA). 
• Background in professional-services, forward-deployed engineering, or AI platform product management. 

Attributes 

• Empathy & Ownership: You listen carefully to user needs and take full ownership of delivering great experiences. 
• Startup Mentality: You move fast, learn quickly, and are comfortable wearing many hats. 
• Detail-Oriented: You care about the little things  
• Mission-Driven: You want to solve important, high-impact problems that matter to real people. 
• Team-Oriented: Low ego, collaborative, and excited to build alongside highly capable engineers, designers, and domain experts.  

Travel:

This position requires the ability to travel to client sites as needed for on-site deployments and collaboration. Travel is estimated at approximately 30–40% of the time (varying by project), and flexibility is expected to accommodate key client engagement activities. 

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

Role Overview

As a Senior Staff Software Engineer at JazzX AI, you will operate as a principal technical owner of the platform’s most critical architectural foundations. This is a highly hands-on, senior individual contributor role with company-wide technical influence.

You will lead the design and evolution of core platform systems, shape long-term technical strategy, and drive execution across multiple teams and domains. Your work will directly influence:

• The long-term architecture of JazzX’s AI-native SaaS + PaaS platform
• How AI capabilities are safely, reliably, and audibly operationalized at scale
• Platform reliability, performance, security, and developer experience
• Engineering standards, architectural principles, and technical decision-making across the organization

This role is for engineers who think in systems, operate with extreme ownership, and enjoy solving ambiguous, high-impact problems at platform scale.

What You Will Do

1. Platform & System Architecture

• Define and evolve the end-to-end architecture for core platform services that power JazzX’s AI-native enterprise system.
• Own architectural decisions across distributed systems, service orchestration, data flows, and platform extensibility.
• Ensure designs balance scalability, reliability, security, privacy, and operational excellence.
• Drive architectural reviews, RFCs, and long-term technical planning across teams.
• Lead the design of enterprise workflows involving multiple services, teams, and human/system interactions
• Use process modeling techniques (e.g., BPMN or equivalent) to clarify flows, ownership, failure paths, and execution semantics

2. Cloud-Native & Infrastructure Foundations

• Set technical direction for cloud-native architecture across compute, storage, networking, and deployment models.
• Champion cloud-first, cloud-agnostic patterns and infrastructure best practices.
• Guide containerization, orchestration, and Infrastructure-as-Code standards.
• Partner closely with SRE, DevOps, and Security teams to build resilient, observable, and cost-efficient systems.

3. Developer Experience & Platform Enablement

• Design and build foundational APIs, frameworks, and abstractions that enable application and AI engineers to move fast without compromising correctness or safety.
• Establish platform contracts, service boundaries, and internal standards for extensibility and reuse.
• Ensure platform components are modular, composable, and well-documented.
• Act as a force multiplier for engineering velocity across the organization.

4. Operational Excellence & Reliability

• Own production readiness for mission-critical platform components, including availability, latency, scalability, and fault isolation.
• Define and enforce SLAs, SLOs, and reliability standards.
• Drive best practices around observability, distributed tracing, alerting, and incident response.
• Continuously improve operational maturity as the platform scales.

5. Technical Leadership & Organizational Influence

• Serve as a senior technical leader influencing platform direction through execution, not hierarchy.
• Mentor Staff and Senior engineers, raising the bar for systems thinking, design quality, and technical rigor.
• Collaborate deeply with AI research, product, security, and design teams to translate complex requirements into robust platform capabilities.
• Act as a trusted technical advisor to senior engineering and product leadership.

What We’re Looking For

Required Qualifications

• 12+ years of experience designing, building, and operating large-scale, production-grade software systems.
• Proven track record of owning and evolving complex distributed systems or platform architectures.
• Deep expertise in cloud-native systems, service-oriented design, and distributed architectures.
• Strong hands-on experience with containerized environments (Docker, Kubernetes) and modern cloud platforms.
•  

Software Engineering Excellence

• Expert-level understanding of software design principles, clean code practices, and system-level trade-offs.
• Strong proficiency in Python, with deep experience in at least one of: Java -Primary , Go, or JavaScript.
• Demonstrated ownership across the full SDLC: design, implementation, testing, deployment, and operations.
• Ability to make sound architectural decisions under ambiguity and evolving requirements.

Platform, Data & Infrastructure Skills

• Experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent).
• Strong understanding of observability stacks, metrics, logging, and distributed tracing.
• Experience with event-driven systems, streaming platforms (e.g., Kafka), and both SQL and NoSQL databases.
• Familiarity with enterprise security, access control, and compliance considerations.
• Experience designing and implementing cross-system workflows (order processing, onboarding, approvals, etc.)
• Hands-on experience with BPMN-based or workflow-driven systems

AI / ML (Strong Plus)

• Experience building or operating platforms that support AI/ML or data-intensive workloads.
• Exposure to MLOps, AI service deployment, or AI-adjacent infrastructure.
• Experience integrating modern AI systems (LLMs, agents, retrieval, evaluation pipelines) into production platforms is a strong plus.

What Sets You Apart

• You think in platforms and systems, not just services.
• You lead through technical depth, execution, and influence, not authority.
• You are comfortable owning decisions with long-term architectural consequences.
• You care deeply about production quality, reliability, and maintainability.
• You thrive in environments where the platform is still being defined.

Staff Software Development Engineer  

As a Staff Software Development Engineer at JazzX AI, you'll define the technical vision for our enterprise AI platform, mentor senior engineers, and oversee the design, development, and deployment of critical AI, software and infra services and components.  You'll be responsible for ensuring the platform's scalability, reliability, security and observability. 

What You Will Do 

Design and Architect Scalable Solutions: 

• Lead the design and development of high-performance, scalable services and components for our enterprise AI platform using a cloud-first, cloud-agnostic approach with world class AI capabilities, scalability, security, privacy and operability.
• Champion a cloud-first, cloud-agnostic approach to ensure platform versatility, scalability, and future-proof architecture.
• Champion innovative AI and software design patterns and best practices to ensure code maintainability, reusability, and testability.
• Contribute to the platform's technical direction by staying up to date on emerging AI technologies, cloud design patterns and user experience methodologies. 

Collaborative Innovation: 

• Foster a collaborative environment by working closely with cross-functional teams (AI/research engineers, software engineers, architects, product managers, and designers) to translate complex platform and product requirements into elegant, scalable, and modular AI, software and infrastructure components.
• Foster a collaborative and inclusive environment by effectively communicating technical concepts and design decisions across diverse audiences.
• Provide mentorship and guidance to junior engineers, fostering their growth and development. 

Driving Operational Excellence: 

• Oversee the seamless integration of components into the platform, ensuring efficient operation, reliability, and a dependable user experience for both customers and partners.
• Champion DevOps and AIOps best practices for AI services, maintainability, performance optimization, and observability. 

Requirements 

• Minimum 10+ years of experience designing, building, and operating cloud-native applications at scale. Expertise in container orchestration frameworks like Kubernetes and containerization technologies like Docker. Expertise in AI/ML/data capabilities, platforms, frameworks and tools.
• Proven track record deploying and managing cloud environments using Infrastructure as Code (IaC) tools like Terraform, Ansible, or CloudFormation.
• Experience in designing and implementing highly available, scalable, and fault-tolerant systems. 

Development Lifecycle: 

• End-to-end ownership of the entire software development lifecycle (SDLC) for complex enterprise platforms and products. This includes experience in design, prototyping, development (including unit, integration, and end-to-end testing), deployment, and ongoing operations. 

Technical Skills: 

• Mastery of essential software development principles with a focus on clean code, design patterns, and best practices.
• In-depth expertise in at least two of the following programming languages: Python, Java, JavaScript, Golang, or C++.
• Solid understanding of distributed systems concepts and experience with distributed tracing tools. 

AI/ML Experience: 

• Demonstrated experience in building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Familiarity with MLOps practices, frameworks (TensorFlow, PyTorch), and tools is a plus 
• Familiarity with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus 

Here’s a summary of the role:

Ready to build real-world AI solutions that actually make an impact?

You’ll take cutting-edge AI and GenAI concepts—like copilots, agents, and intelligent workflows—and turn them into scalable, production-ready systems used across sales, finance, customer success, and more. If you enjoy hands-on backend engineering, working with APIs, cloud platforms, and LLMs, and transforming ideas into high-performing AI-driven products, this role puts you right at the center of innovation.

Here’s a breakdown of what you’ll do (not all of it, just the important stuff):

• Build and scale backend services, APIs, and integrations that embed AI/GenAI into enterprise systems (CRM, ERP, BI)
• Develop LLM-powered solutions such as RAG pipelines, copilots, agents, and automation workflows
• Take AI solutions from concept to production—design, build, test, deploy, and monitor
• Collaborate with architects and business stakeholders to turn requirements into practical AI implementations
• Create and manage data pipelines to enable reliable, high-quality AI workflows
• Ensure solutions are secure, scalable, observable, and aligned with best practices

These are the essentials you’ll need to get an interview:

• 5+ years of experience in software or solutions engineering with production systems
• Strong programming skills in Python, Java, C#, or Node.js
• Hands-on experience with APIs, integrations (REST/webhooks), and backend development
• Practical experience working with LLMs/GenAI tools (e.g., OpenAI, LangChain, or similar)
• Experience with cloud platforms (preferably AWS), CI/CD, and containerization
• Solid understanding of AI/GenAI concepts like prompt engineering, RAG, or agents
• Ability to translate technical solutions into business impact and collaborate across teams

It would be great if you had these too, but we’ll support you if you don’t:

• Experience integrating AI into CRM, ERP, or analytics platforms
• Familiarity with MLOps/LLMOps concepts such as model lifecycle and monitoring
• Exposure to machine learning or data analytics tools (e.g., Scikit-learn, dashboards)
• Experience working in global or distributed teams
• Knowledge of AI governance, security, and responsible AI practices

Title: DevOps Engineer

Reporting to: Senior Director, Product Development
Location: Bengaluru (Bangalore)

Opportunity:

Responsibilities:

Infrastructure Development & Integration

• Design, implement, and manage cloud-native infrastructure (AWS, Azure, GCP) to support healthcare platforms, AI agents, and clinical applications.
• Build and maintain scalable CI/CD pipelines to enable rapid and reliable delivery of software, data pipelines, and AI/ML models.
• Design and manage Kubernetes (K8s) clusters for container orchestration, workload scaling, and high availability with integrated monitoring to ensure cluster health and performance
• Implement Kubernetes-native tools (Helm, Kustomize, ArgoCD) for deployment automation and environment management ensuring observability through monitoring dashboards and alerts
• Collaborate with Staff Engineers/Architects to align infrastructure with enterprise goals for scalability, reliability, and performance leveraging monitoring insights to inform architectural decisions.

System Optimization & Reliability

• Implement and maintain comprehensive monitoring, logging, and alerting mechanisms (Prometheus, Grafana, ELK, Datadog, AWS cloudwatch, AWS cloud trail) to ensure real-time visibility into system performance, resource utilization, and potential incidents.
• Implement monitoring, logging, and alerting mechanisms (Prometheus, Grafana, ELK, Datadog) to ensure system reliability and proactive incident response.
• Ensure data pipeline workflows (ETL/ELT, real-time streaming, batch processing) are observable, reliable, and auditable.
• Support observability and monitoring of GenAI pipelines, embeddings, vector databases, and agentic AI workflows.
• Proactively analyze monitoring data to identify bottlenecks, predict failures, and drive continuous improvement in system reliability.

Compliance & Security

• Support audit trails and compliance reporting through automated DevSecOps practices.
• Implement security controls for LLM-based applications, AI agents, and healthcare data pipelines, including prompt injection prevention, API rate limiting, and data governance.

Collaboration & Agile Practices

• Partner closely with software engineers, data engineers, AI/ML engineers, and product managers to deliver integrated, secure, and scalable solutions.
• Contribute to agile development processes including sprint planning, stand-ups, and retrospectives.
• Mentor junior engineers and share best practices in cloud-native infrastructure, CI/CD, Kubernetes, and automation.

Innovation & Technical Expertise

• Stay informed about emerging DevOps practices, cloud-native architectures, MLOps/LLMOps, and data engineering tools.
• Prototype and evaluate new frameworks and tools to enhance infrastructure for data pipelines, GenAI, and Agentic AI applications.
• Advocate for best practices in infrastructure design, focusing on modularity, maintainability, and scalability.

Requirements

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical discipline.
• 6+ years of experience in DevOps, Site Reliability Engineering, or related roles, with at least 3+ years building cloud-native infrastructure.
• Proven track record of managing production-grade Kubernetes clusters and cloud infrastructure in regulated environments.
• Experience supporting GenAI/LLM applications (e.g., OpenAI, Hugging Face, LangChain) and vector databases (e.g., Pinecone, Weaviate, FAISS).
• Hands-on experience supporting data pipeline products using ETL/ELT frameworks (Apache Airflow, dbt, Prefect) and streaming systems (Kafka, Spark, Flink).
• Experience deploying AI agents and orchestrating agent workflows in production environments.

Technical Proficiency

• Expertise in Kubernetes (K8s) for orchestration, scaling, and managing containerized applications.
• Strong proficiency in containerization (Docker) and Kubernetes ecosystem tools (Helm, ArgoCD, Istio/Linkerd for service mesh).
• Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, or Pulumi).
• Proficiency with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, ArgoCD, Spinnaker).
• Familiarity with monitoring and observability tools (Prometheus, Grafana, ELK, Datadog, AWS cloud watch and AWS cloud trail), including setting up dashboards, alerts, and custom metrics for cloud-native and AI systems.
• Good to have: knowledge of healthcare data standards (FHIR, HL7) and secure deployment practices for AI/ML and data pipelines.

Professional Skills

• Strong problem-solving skills with a focus on reliability, scalability, and security.
• Excellent collaboration and communication skills across cross-functional teams.
• Proactive, detail-oriented, and committed to technical excellence in a fast-paced healthcare environment.

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

• SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
• Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
• TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

Role Overview

As a Senior Staff Software Engineer at JazzX AI, you will operate as a principal technical owner of the platform’s most critical architectural foundations. This is a highly hands-on, senior individual contributor role with company-wide technical influence.

You will lead the design and evolution of core platform systems, shape long-term technical strategy, and drive execution across multiple teams and domains. Your work will directly influence:

• The long-term architecture of JazzX’s AI-native SaaS + PaaS platform
• How AI capabilities are safely, reliably, and audibly operationalized at scale
• Platform reliability, performance, security, and developer experience
• Engineering standards, architectural principles, and technical decision-making across the organization

This role is for engineers who think in systems, operate with extreme ownership, and enjoy solving ambiguous, high-impact problems at platform scale.

What You Will Do

1. Platform & System Architecture

• Define and evolve the end-to-end architecture for core platform services that power JazzX’s AI-native enterprise system.
• Own architectural decisions across distributed systems, service orchestration, data flows, and platform extensibility.
• Ensure designs balance scalability, reliability, security, privacy, and operational excellence.
• Drive architectural reviews, RFCs, and long-term technical planning across teams.
• Lead the design of enterprise workflows involving multiple services, teams, and human/system interactions
• Use process modeling techniques (e.g., BPMN or equivalent) to clarify flows, ownership, failure paths, and execution semantics

2. Cloud-Native & Infrastructure Foundations

• Set technical direction for cloud-native architecture across compute, storage, networking, and deployment models.
• Champion cloud-first, cloud-agnostic patterns and infrastructure best practices.
• Guide containerization, orchestration, and Infrastructure-as-Code standards.
• Partner closely with SRE, DevOps, and Security teams to build resilient, observable, and cost-efficient systems.

3. Developer Experience & Platform Enablement

• Design and build foundational APIs, frameworks, and abstractions that enable application and AI engineers to move fast without compromising correctness or safety.
• Establish platform contracts, service boundaries, and internal standards for extensibility and reuse.
• Ensure platform components are modular, composable, and well-documented.
• Act as a force multiplier for engineering velocity across the organization.

4. Operational Excellence & Reliability

• Own production readiness for mission-critical platform components, including availability, latency, scalability, and fault isolation.
• Define and enforce SLAs, SLOs, and reliability standards.
• Drive best practices around observability, distributed tracing, alerting, and incident response.
• Continuously improve operational maturity as the platform scales.

5. Technical Leadership & Organizational Influence

• Serve as a senior technical leader influencing platform direction through execution, not hierarchy.
• Mentor Staff and Senior engineers, raising the bar for systems thinking, design quality, and technical rigor.
• Collaborate deeply with AI research, product, security, and design teams to translate complex requirements into robust platform capabilities.
• Act as a trusted technical advisor to senior engineering and product leadership.

What We’re Looking For

Required Qualifications

• 12+ years of experience designing, building, and operating large-scale, production-grade software systems.
• Proven track record of owning and evolving complex distributed systems or platform architectures.
• Deep expertise in cloud-native systems, service-oriented design, and distributed architectures.
• Strong hands-on experience with containerized environments (Docker, Kubernetes) and modern cloud platforms.
•  

Software Engineering Excellence

• Expert-level understanding of software design principles, clean code practices, and system-level trade-offs.
• Strong proficiency in Python, with deep experience in at least one of: Java -Primary , Go, or JavaScript.
• Demonstrated ownership across the full SDLC: design, implementation, testing, deployment, and operations.
• Ability to make sound architectural decisions under ambiguity and evolving requirements.

Platform, Data & Infrastructure Skills

• Experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent).
• Strong understanding of observability stacks, metrics, logging, and distributed tracing.
• Experience with event-driven systems, streaming platforms (e.g., Kafka), and both SQL and NoSQL databases.
• Familiarity with enterprise security, access control, and compliance considerations.
• Experience designing and implementing cross-system workflows (order processing, onboarding, approvals, etc.)
• Hands-on experience with BPMN-based or workflow-driven systems

AI / ML (Strong Plus)

• Experience building or operating platforms that support AI/ML or data-intensive workloads.
• Exposure to MLOps, AI service deployment, or AI-adjacent infrastructure.
• Experience integrating modern AI systems (LLMs, agents, retrieval, evaluation pipelines) into production platforms is a strong plus.

What Sets You Apart

• You think in platforms and systems, not just services.
• You lead through technical depth, execution, and influence, not authority.
• You are comfortable owning decisions with long-term architectural consequences.
• You care deeply about production quality, reliability, and maintainability.
• You thrive in environments where the platform is still being defined.

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The Opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The Role  

As a Artificial Intelligence (AI) - Technical Lead, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 10+ Years of experience, a growth mindset and a drive to make a lasting impact. 

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Role Responsibilities

• As an AI Tech Lead, you will help design, build, and optimize AI-first systems and solutions that advance our digital capabilities and create real value for our clients.
• Provide technical leadership and mentorship to a multidisciplinary AI team.
• Collaborate with stakeholders to identify business opportunities and AI use cases.
• Translate abstract business problems into concrete, innovative AI solutions.
• Drive code quality, robust architecture, and documentation within technical teams.
• Facilitate knowledge sharing, peer reviews, and upskilling within the AI team.
• You will collaborate with cross-functional teams.
• Work on Valtech’s various AI Accelerators 

Must have qualifications

To be considered for this role, you must meet the following essential qualifications: 

• 3+ years of hands-on experience in AI engineering and 10+ years of overall work experience.
• Proficiency with programming languages such as Python.
• Knowledge of software engineering best practices including source control, CI/CD, and automated testing.
• Familiarity with cloud technologies and managed AI services such as Azure Machine Learning, AWS SageMaker, or Google AI Platform.
• Understanding of responsible AI, data privacy, and ethical AI development.
• Understanding of AI Concepts like LLMs, RAG, AgenticAI, MCPs. Stay updated with the latest AI research and technologies.
• Prior involvement in MLOps, model deployment, monitoring, and automation of AI workflows.
• Strong critical thinking, communication, and teamwork skills, with a willingness to share ideas and collaborate.
• Zeal to learn & Excel.

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

The benefits  

This is a Full Time position based in Bengaluru/Pune/ Ahmedabad /Gurugram in India.

Beyond a competitive compensation package, we offer: 

• Flexibility, with remote and hybrid work options (country-dependent) 
• Career advancement, with international mobility and professional development programs 
• Learning and development, with access to cutting-edge tools, training and industry experts 

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. 

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses ending in @valtech.com. 

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

Position Overview

We are seeking a Computer Vision AI & ML Engineer to design, build, and deploy advanced perception systems for real-world robotics and automation. You will work across the full machine learning lifecycle—model development, data strategy, evaluation, and production integration—to deliver robust, high-performance vision capabilities. This role combines applied research with hands-on engineering and offers the opportunity to influence both architecture and roadmap decisions.

Responsibilities

• Develop and optimize deep learning models for object detection, segmentation, tracking, and 3D scene understanding using multi-modal sensor data.
• Build scalable pipelines for data processing, training, evaluation, and deployment into real-world and real-time systems.
• Design labeling strategies and tooling for automated annotation, QA workflows, dataset management, augmentation, and versioning.
• Implement monitoring and reliability frameworks, including uncertainty estimation, failure detection, and automated performance reporting.
• Conduct proof-of-concept experiments to evaluate new algorithms and perception techniques; translate research insights into practical prototypes.
• Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.

Preferred Qualifications

• Strong experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
• Background in computer vision tasks such as detection, segmentation, tracking, or 3D scene understanding.
• Proficiency in Python; familiarity with C++ is a plus.
• Experience building training pipelines, evaluation frameworks, and ML deployment workflows.
• Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo).
• Experience with data annotation tools, dataset management, and augmentation techniques.
• Familiarity with robotics, simulation environments (Isaac Sim, Gazebo, Blender), or real-time systems.
• Understanding of uncertainty modeling, reliability engineering, or ML monitoring/MLOps practices.

Role Overview

As a Senior Staff Software Engineer at JazzX AI, you will operate as a principal technical owner of the platform’s most critical architectural foundations. This is a highly hands-on, senior individual contributor role with company-wide technical influence.

You will lead the design and evolution of core platform systems, shape long-term technical strategy, and drive execution across multiple teams and domains. Your work will directly influence:

• The long-term architecture of JazzX’s AI-native SaaS + PaaS platform
• How AI capabilities are safely, reliably, and audibly operationalized at scale
• Platform reliability, performance, security, and developer experience
• Engineering standards, architectural principles, and technical decision-making across the organization

This role is for engineers who think in systems, operate with extreme ownership, and enjoy solving ambiguous, high-impact problems at platform scale.

What You Will Do

1. Platform & System Architecture

• Define and evolve the end-to-end architecture for core platform services that power JazzX’s AI-native enterprise system.
• Own architectural decisions across distributed systems, service orchestration, data flows, and platform extensibility.
• Ensure designs balance scalability, reliability, security, privacy, and operational excellence.
• Drive architectural reviews, RFCs, and long-term technical planning across teams.
• Lead the design of enterprise workflows involving multiple services, teams, and human/system interactions
• Use process modeling techniques (e.g., BPMN or equivalent) to clarify flows, ownership, failure paths, and execution semantics

2. Cloud-Native & Infrastructure Foundations

• Set technical direction for cloud-native architecture across compute, storage, networking, and deployment models.
• Champion cloud-first, cloud-agnostic patterns and infrastructure best practices.
• Guide containerization, orchestration, and Infrastructure-as-Code standards.
• Partner closely with SRE, DevOps, and Security teams to build resilient, observable, and cost-efficient systems.

3. Developer Experience & Platform Enablement

• Design and build foundational APIs, frameworks, and abstractions that enable application and AI engineers to move fast without compromising correctness or safety.
• Establish platform contracts, service boundaries, and internal standards for extensibility and reuse.
• Ensure platform components are modular, composable, and well-documented.
• Act as a force multiplier for engineering velocity across the organization.

4. Operational Excellence & Reliability

• Own production readiness for mission-critical platform components, including availability, latency, scalability, and fault isolation.
• Define and enforce SLAs, SLOs, and reliability standards.
• Drive best practices around observability, distributed tracing, alerting, and incident response.
• Continuously improve operational maturity as the platform scales.

5. Technical Leadership & Organizational Influence

• Serve as a senior technical leader influencing platform direction through execution, not hierarchy.
• Mentor Staff and Senior engineers, raising the bar for systems thinking, design quality, and technical rigor.
• Collaborate deeply with AI research, product, security, and design teams to translate complex requirements into robust platform capabilities.
• Act as a trusted technical advisor to senior engineering and product leadership.

What We’re Looking For

Required Qualifications

• 12+ years of experience designing, building, and operating large-scale, production-grade software systems.
• Proven track record of owning and evolving complex distributed systems or platform architectures.
• Deep expertise in cloud-native systems, service-oriented design, and distributed architectures.
• Strong hands-on experience with containerized environments (Docker, Kubernetes) and modern cloud platforms.
•  

Software Engineering Excellence

• Expert-level understanding of software design principles, clean code practices, and system-level trade-offs.
• Strong proficiency in Python, with deep experience in at least one of: Java -Primary , Go, or JavaScript.
• Demonstrated ownership across the full SDLC: design, implementation, testing, deployment, and operations.
• Ability to make sound architectural decisions under ambiguity and evolving requirements.

Platform, Data & Infrastructure Skills

• Experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent).
• Strong understanding of observability stacks, metrics, logging, and distributed tracing.
• Experience with event-driven systems, streaming platforms (e.g., Kafka), and both SQL and NoSQL databases.
• Familiarity with enterprise security, access control, and compliance considerations.
• Experience designing and implementing cross-system workflows (order processing, onboarding, approvals, etc.)
• Hands-on experience with BPMN-based or workflow-driven systems

AI / ML (Strong Plus)

• Experience building or operating platforms that support AI/ML or data-intensive workloads.
• Exposure to MLOps, AI service deployment, or AI-adjacent infrastructure.
• Experience integrating modern AI systems (LLMs, agents, retrieval, evaluation pipelines) into production platforms is a strong plus.

What Sets You Apart

• You think in platforms and systems, not just services.
• You lead through technical depth, execution, and influence, not authority.
• You are comfortable owning decisions with long-term architectural consequences.
• You care deeply about production quality, reliability, and maintainability.
• You thrive in environments where the platform is still being defined.

Staff Software Development Engineer  

As a Staff Software Development Engineer at JazzX AI, you'll define the technical vision for our enterprise AI platform, mentor senior engineers, and oversee the design, development, and deployment of critical AI, software and infra services and components.  You'll be responsible for ensuring the platform's scalability, reliability, security and observability. 

What You Will Do 

Design and Architect Scalable Solutions: 

• Lead the design and development of high-performance, scalable services and components for our enterprise AI platform using a cloud-first, cloud-agnostic approach with world class AI capabilities, scalability, security, privacy and operability.
• Champion a cloud-first, cloud-agnostic approach to ensure platform versatility, scalability, and future-proof architecture.
• Champion innovative AI and software design patterns and best practices to ensure code maintainability, reusability, and testability.
• Contribute to the platform's technical direction by staying up to date on emerging AI technologies, cloud design patterns and user experience methodologies. 

Collaborative Innovation: 

• Foster a collaborative environment by working closely with cross-functional teams (AI/research engineers, software engineers, architects, product managers, and designers) to translate complex platform and product requirements into elegant, scalable, and modular AI, software and infrastructure components.
• Foster a collaborative and inclusive environment by effectively communicating technical concepts and design decisions across diverse audiences.
• Provide mentorship and guidance to junior engineers, fostering their growth and development. 

Driving Operational Excellence: 

• Oversee the seamless integration of components into the platform, ensuring efficient operation, reliability, and a dependable user experience for both customers and partners.
• Champion DevOps and AIOps best practices for AI services, maintainability, performance optimization, and observability. 

Requirements 

• Minimum 8+ years of experience designing, building, and operating cloud-native applications at scale. Expertise in container orchestration frameworks like Kubernetes and containerization technologies like Docker. Expertise in AI/ML/data capabilities, platforms, frameworks and tools.
• Proven track record deploying and managing cloud environments using Infrastructure as Code (IaC) tools like Terraform, Ansible, or CloudFormation.
• Experience in designing and implementing highly available, scalable, and fault-tolerant systems. 

Development Lifecycle: 

• End-to-end ownership of the entire software development lifecycle (SDLC) for complex enterprise platforms and products. This includes experience in design, prototyping, development (including unit, integration, and end-to-end testing), deployment, and ongoing operations. 

Technical Skills: 

• Mastery of essential software development principles with a focus on clean code, design patterns, and best practices.
• In-depth expertise in at least two of the following programming languages: Python, Java, JavaScript, Golang, or C++.
• Solid understanding of distributed systems concepts and experience with distributed tracing tools. 

AI/ML Experience: 

• Demonstrated experience in building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Familiarity with MLOps practices, frameworks (TensorFlow, PyTorch), and tools is a plus 
• Familiarity with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus 

Role Overview

As a Senior Staff Software Engineer at JazzX AI, you will operate as a principal technical owner of the platform’s most critical architectural foundations. This is a highly hands-on, senior individual contributor role with company-wide technical influence.

You will lead the design and evolution of core platform systems, shape long-term technical strategy, and drive execution across multiple teams and domains. Your work will directly influence:

• The long-term architecture of JazzX’s AI-native SaaS + PaaS platform
• How AI capabilities are safely, reliably, and audibly operationalized at scale
• Platform reliability, performance, security, and developer experience
• Engineering standards, architectural principles, and technical decision-making across the organization

This role is for engineers who think in systems, operate with extreme ownership, and enjoy solving ambiguous, high-impact problems at platform scale.

What You Will Do

1. Platform & System Architecture

• Define and evolve the end-to-end architecture for core platform services that power JazzX’s AI-native enterprise system.
• Own architectural decisions across distributed systems, service orchestration, data flows, and platform extensibility.
• Ensure designs balance scalability, reliability, security, privacy, and operational excellence.
• Drive architectural reviews, RFCs, and long-term technical planning across teams.
• Lead the design of enterprise workflows involving multiple services, teams, and human/system interactions
• Use process modeling techniques (e.g., BPMN or equivalent) to clarify flows, ownership, failure paths, and execution semantics

2. Cloud-Native & Infrastructure Foundations

• Set technical direction for cloud-native architecture across compute, storage, networking, and deployment models.
• Champion cloud-first, cloud-agnostic patterns and infrastructure best practices.
• Guide containerization, orchestration, and Infrastructure-as-Code standards.
• Partner closely with SRE, DevOps, and Security teams to build resilient, observable, and cost-efficient systems.

3. Developer Experience & Platform Enablement

• Design and build foundational APIs, frameworks, and abstractions that enable application and AI engineers to move fast without compromising correctness or safety.
• Establish platform contracts, service boundaries, and internal standards for extensibility and reuse.
• Ensure platform components are modular, composable, and well-documented.
• Act as a force multiplier for engineering velocity across the organization.

4. Operational Excellence & Reliability

• Own production readiness for mission-critical platform components, including availability, latency, scalability, and fault isolation.
• Define and enforce SLAs, SLOs, and reliability standards.
• Drive best practices around observability, distributed tracing, alerting, and incident response.
• Continuously improve operational maturity as the platform scales.

5. Technical Leadership & Organizational Influence

• Serve as a senior technical leader influencing platform direction through execution, not hierarchy.
• Mentor Staff and Senior engineers, raising the bar for systems thinking, design quality, and technical rigor.
• Collaborate deeply with AI research, product, security, and design teams to translate complex requirements into robust platform capabilities.
• Act as a trusted technical advisor to senior engineering and product leadership.

What We’re Looking For

Required Qualifications

• 12+ years of experience designing, building, and operating large-scale, production-grade software systems.
• Proven track record of owning and evolving complex distributed systems or platform architectures.
• Deep expertise in cloud-native systems, service-oriented design, and distributed architectures.
• Strong hands-on experience with containerized environments (Docker, Kubernetes) and modern cloud platforms.
•  

Software Engineering Excellence

• Expert-level understanding of software design principles, clean code practices, and system-level trade-offs.
• Strong proficiency in Python, with deep experience in at least one of: Java -Primary , Go, or JavaScript.
• Demonstrated ownership across the full SDLC: design, implementation, testing, deployment, and operations.
• Ability to make sound architectural decisions under ambiguity and evolving requirements.

Platform, Data & Infrastructure Skills

• Experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent).
• Strong understanding of observability stacks, metrics, logging, and distributed tracing.
• Experience with event-driven systems, streaming platforms (e.g., Kafka), and both SQL and NoSQL databases.
• Familiarity with enterprise security, access control, and compliance considerations.
• Experience designing and implementing cross-system workflows (order processing, onboarding, approvals, etc.)
• Hands-on experience with BPMN-based or workflow-driven systems

AI / ML (Strong Plus)

• Experience building or operating platforms that support AI/ML or data-intensive workloads.
• Exposure to MLOps, AI service deployment, or AI-adjacent infrastructure.
• Experience integrating modern AI systems (LLMs, agents, retrieval, evaluation pipelines) into production platforms is a strong plus.

What Sets You Apart

• You think in platforms and systems, not just services.
• You lead through technical depth, execution, and influence, not authority.
• You are comfortable owning decisions with long-term architectural consequences.
• You care deeply about production quality, reliability, and maintainability.
• You thrive in environments where the platform is still being defined.

About JazzX AI

JazzX AI delivers value across the full AI application lifecycle:

1. Next-Generation Enterprise AI Platform A production-grade AI platform that orchestrates foundation models, reasoning systems, agents, retrieval, evaluation, and guardrails—designed for reliability, safety, and scale.

1. AI Builder Studio (Low-Code / No-Code)

A modern Builder Studio enabling developers and non-developers to design, compose, and deploy AI-powered workflows using visual and declarative abstractions .

1. First-Party Enterprise Applications Customer-facing enterprise applications built on the same platform, ensuring dogfooding, rapid iteration, and real-world validation at scale. We are starting with residential lending—a domain defined by deep due diligence, complex policies, and expert judgment—and are building a horizontal AI platform that will extend across knowledge-intensive industries.

Role Overview

As a Senior Staff Software Engineer at JazzX AI, you will operate as a principal technical owner of the platformʼs most critical architectural foundations. This is a highly hands-on, senior individual contributor role with company-wide technical influence.

You will lead the design and evolution of core platform systems, shape long term technical strategy, and drive execution across multiple teams and domains. Your work will directly influence:

• The long-term architecture of JazzXʼs AI-native SaaS + PaaS platform
• How AI capabilities are safely, reliably, and audibly operationalized at scale
• Platform reliability, performance, security, and developer experience
• Engineering standards, architectural principles, and technical decision making across the organization

This role is for engineers who think in systems, operate with extreme ownership, and enjoy solving ambiguous, high-impact problems at platform scale.

What You Will Do

1. Platform & System Architecture

• Define and evolve the end-to-end architecture for core platform services that power JazzXʼs AI-native enterprise system.
• Own architectural decisions across distributed systems, service orchestration, data flows, and platform extensibility.
• Ensure designs balance scalability, reliability, security, privacy, and operational excellence .
• Drive architectural reviews, RFCs, and long-term technical planning across teams.
• Lead the design of enterprise workflows involving multiple services, teams, and human/system interactions .
• Use process modeling techniques (e.g., BPMN or equivalent) to clarify flows, ownership, failure paths, and execution semantics.

1. Cloud-Native & Infrastructure Foundations

• Set technical direction for cloud-native architecture across compute, storage, networking, and deployment models.
• Champion cloud-first, cloud-agnostic patterns and infrastructure best practices.
• Guide containerization, orchestration, and Infrastructure-as-Code standards.
• Partner closely with SRE, DevOps, and Security teams to build resilient, observable, and cost-efficient systems.

1. Developer Experience & Platform Enablement

• Design and build foundational APIs, frameworks, and abstractions that enable application and AI engineers to move fast without compromising correctness or safety.
• Establish platform contracts, service boundaries, and internal standards for extensibility and reuse.
• Ensure platform components are modular, composable, and well documented.
• Act as a force multiplier for engineering velocity across the organization.

1. Operational Excellence & Reliability

• Own production readiness for mission-critical platform components, including availability, latency, scalability, and fault isolation.
• Define and enforce SLAs, SLOs, and reliability standards.
• Drive best practices around observability, distributed tracing, alerting, and incident response.
• Continuously improve operational maturity as the platform scales.

1. Technical Leadership & Organizational Influence

• Serve as a senior technical leader influencing platform direction through execution, not hierarchy.
• Mentor Staff and Senior engineers, raising the bar for systems thinking, design quality, and technical rigor.
• Collaborate deeply with AI research, product, security, and design teams to translate complex requirements into robust platform capabilities.
• Act as a trusted technical advisor to senior engineering and product leadership.

What Weʼre Looking For

Required Qualifications

• 12+ years of experience designing, building, and operating large-scale, production-grade software systems.
• Proven track record of owning and evolving complex distributed systems or platform architectures.
• Deep expertise in cloud-native systems, service-oriented design, and distributed architectures.
• Strong hands-on experience with containerized environments Docker, Kubernetes) and modern cloud platforms.

Software Engineering Excellence

• Expert-level understanding of software design principles, clean code practices, and system-level trade-offs.
• Strong proficiency in Python, with deep experience in at least one of: Java -Primary , Go, or JavaScript.
• Demonstrated ownership across the full SDLC: design, implementation, testing, deployment, and operations.
• Ability to make sound architectural decisions under ambiguity and evolving requirements.

Platform, Data & Infrastructure Skills

• Experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent).
• Strong understanding of observability stacks, metrics, logging, and distributed tracing.
• Experience with event-driven systems, streaming platforms (e.g., Kafka), and both SQL and NoSQL databases.
• Familiarity with enterprise security, access control, and compliance considerations.
• Experience designing and implementing cross-system workflows (order processing, onboarding, approvals, etc.)
• Hands-on experience with BPMN-based or workflow-driven systems .

AI / ML (Strong Plus)

• Experience building or operating platforms that support AI/ML or data intensive workloads.
• Exposure to MLOps, AI service deployment, or AI-adjacent infrastructure.
• Experience integrating modern AI systems (LLMs, agents, retrieval, evaluation pipelines) into production platforms is a strong plus.

What Sets You Apart

• You think in platforms and systems, not just services.
• You lead through technical depth, execution, and influence, not authority.
• You are comfortable owning decisions with long-term architectural consequences.
• You care deeply about production quality, reliability, and maintainability.
• You thrive in environments where the platform is still being defined.

Senior Staff Engineer

As a Senior Staff Engineer at JazzX AI, you will operate as a strategic technical leader—driving platform architecture, guiding critical projects, and influencing product direction.  You will serve as a hands-on contributor, provide technical mentorship across teams, and partner with senior stakeholders to ensure our solutions are innovative, robust, and aligned with the company’s long-term vision. You will also be instrumental in fostering a high-performance engineering culture that emphasizes collaboration, excellence, and continuous improvement. 

Key Responsibilities 

Technical Leadership & Architecture 

• Define and evolve JazzX.ai’s technical strategy, ensuring our AI-driven systems can scale and adapt to future challenges.
• Own the end-to-end architecture for key platform components, ensuring high levels of reliability, security, and performance.
• Evaluate emerging technologies, tools, and frameworks, making data-driven recommendations that influence company-wide engineering decisions. 

Project Execution & Cross-Functional Collaboration 

• Lead complex, high-impact engineering initiatives that require coordination across multiple product and infrastructure teams.
• Collaborate with Product Management, AI research engineering, , and UX to scope technical requirements and deliver solutions that align with business objectives.
• Serve as a trusted advisor to senior stakeholders, clearly communicating technical roadmaps, trade-offs, and risks. 

Mentorship & Team Development 

• Guide and mentor engineers at all levels, from early-career to senior staff, providing technical direction and career development support.
• Champion best practices in code quality, architecture reviews, testing, and documentation.
• Foster an inclusive and innovative engineering culture, encouraging knowledge-sharing and continuous learning. 

Innovation & AI Integration 

• Partner with the AI research engineering team team to design and implement modern AI frameworks and capabilities  as production services in the platform
• Drive the exploration and adoption of state-of-the-art AI/ML technologies to keep JazzX.ai ahead of industry trends.
• Identify strategic opportunities where AI can deliver enhanced functionality or novel capabilities for our platform. 

Operational Excellence 

• Define and enforce SLAs for mission-critical services, ensuring minimal downtime and fast recovery.
• Champion DevOps best practices around CI/CD, cloud infrastructure, observability, and security.
• Collaborate with Site Reliability Engineers (SREs) and Security teams to optimize performance and maintain compliance with industry standards. 

 Qualifications 

Educational Background 

• Bachelor’s or Master’s in Computer Science, Engineering, or a related field; or equivalent experience. 

Experience & Technical Expertise 

• 10–12+ years of professional software engineering experience, with at least 5 years in technical leadership roles (Principal, Staff, or equivalent).
• Proven track record leading complex, large-scale projects across distributed systems, backend architecture, or cloud platforms.
• Deep expertise in at least one or more programming languages (e.g., Python, Java, Javascript, Go,  C++), with a willingness to learn new technologies.
• Strong understanding of microservices, event-driven architectures, and container orchestration tools (Kubernetes, Docker).
• Experience with large-scale data processing, streaming platforms (e.g., Kafka), and databases (both SQL and NoSQL).
• Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and operationalizing machine learning solutions is a plus. 

AI/ML Experience: 

• Demonstrated experience in designing, building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Hands on experience with MLOps practices, frameworks (TensorFlow, PyTorch), and tools. 
• Experience building platforms and applications with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus 

Leadership & Soft Skills 

• Exceptional communication and presentation skills, with the ability to influence technical and non-technical stakeholders at executive levels.
• Proven ability to mentor, coach, and inspire engineers, build high-performing teams and a culture of engineering excellence.
• Experience navigating ambiguous requirements and delivering results in a fast-paced, startup environment.
• Demonstrated thought leadership in architectural design, code quality, and technical strategy. 

About SAI Group

SAI Group is a private investment firm that has committed $1 billion to incubate and scale revolutionary AI-powered enterprise software application companies. Our portfolio, a testament to our success, comprises rapidly growing AI companies that collectively cater to over 2,000+ major global customers, approaching $750 million in annual revenue, and employing a global workforce of over 4,000 individuals.

SAI Group invests in new ventures based on breakthrough AI-based products that have the potential to disrupt existing enterprise software markets. SAI Group’s latest investment, JazzX, is a pioneering technology company which is building a platform that will not only shape the future of enterprise AI applications but also offer practical solutions to real-world challenges.

Senior Software Engineer, JazzX (New AI Venture at SAI Group) 

Role Overview:  

As a Senior Software Development Engineer, you'll lead the design, development, and management of critical services and components of an innovative enterprise AI platform to deliver transformative, AI-enabled work experiences for enterprise users. You'll mentor junior engineers, collaborate with cross-functional teams, and drive towards building a cutting-edge enterprise AI platform that remains state of the art.  

Design and Build: 

• Craft and develop high-performance, scalable services and components for our enterprise AI platform using a cloud-first, cloud-agnostic approach with world class AI capabilities, scalability, security, privacy and operability.
• Champion innovative AI and software design patterns and best practices to ensure code maintainability, reusability, and testability.
• Contribute to the platform's technical direction by staying up to date on emerging AI technologies, cloud design patterns and user experience methodologies. 

Collaboration: 

• Work collaboratively within a cross-functional team (AI/research engineers, software engineers, architects, product managers, designers) to translate complex platform and product requirements into well-defined, scalable, and modular AI, software and infrastructure components.
• Foster a collaborative and inclusive environment by effectively communicating technical concepts and design decisions across diverse audiences.
• Provide mentorship and guidance to junior engineers, fostering their growth and development. 

Operational Excellence: 

• Own the seamless integration of developed components into the platform, ensuring efficient operation and high availability.
• Implement robust monitoring and alerting strategies to proactively identify and troubleshoot potential issues.
• Champion DevOps practices streamlining the software development lifecycle and delivery process. 

Requirements 

Experience:  

• Minimum of 5 years in designing, building, and operating cloud services, with proficiency in container and orchestration frameworks such as Docker and Kubernetes. Experience with common software defined infrastructure (infrastructure-as-code) frameworks to deploy and manage cloud environments. AI/ML/Data experience is strongly preferred. 

 Development Lifecycle:  

• Comprehensive hands-on experience in the full-stack development lifecycle, including design, prototyping, building, testing, deployment, and operations of enterprise platforms and products, preferably with AI/ML/data components. 

 Technical Skills:  

• Deep knowledge of essential software development skills and experience in more than 1 of the following languages: Java, JavaScript, Python, Golang, or C++.
• AI/ML Experience (Strongly Preferred): Prior experience in building and managing ML/AI platforms and services, including familiarity with MLOps lifecycle, frameworks, and tools. Familiarity with modern GenAI/LLM services, AI agent frameworks like LangChain, LlamaIndex is highly desired.  
• Growth Mindset: A naturally curious attitude with a proactive approach to learning, experimenting, building, operating, and improving the development of a cutting-edge intelligent platform. Flexible, learn-it-all attitude, encouraging sharing and collaborative growth in an intense and fun work environment. 

Why Join Us 

At JazzX AI, you have the opportunity to become an integral part of a pioneering team that is pushing the envelope of AI capabilities to create an autonomous intelligence driven future. We champion bold innovation, continuous learning, and embrace the challenges and rewards of crafting something genuinely groundbreaking.

Your work will directly contribute to pioneering solutions that have the potential to transform industries and redefine how we interact with technology. As an early member of our team, your voice will be pivotal in steering the direction of our projects and culture, offering a unique chance to leave your mark on the future of AI.

We offer a competitive salary, equity options, and an attractive benefits package, including health, dental, and vision insurance, flexible working arrangements, and more.

We are an equal opportunity employer and celebrate diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

About the Role

Join us as a Full Stack Staff Engineer to lead the evolution of the AlphaSense Application Portfolio through robust architecture and cutting-edge AI integration. This role is designed for a seasoned engineer who thrives on solving massive-scale frontend challenges and building performant, customer-focused systems. You will act as a strategic lead—researching and architecting solutions for complex frontends, while fostering a culture of technical excellence across the team. If you are looking to combine hands-on AI innovation with high-impact organizational leadership, this role is for you.

What You’ll Do:

• Serve as the Architectural Anchor for integrating AI into the product fabric. You will research, prototype, and deploy cutting-edge solutions using LLMs and the latest frontend technologies, ensuring these models are not just theoretical but are seamlessly integrated into high-performance, user-facing applications.
• Design the frontend architecture that serves as the gateway to our AI platform. You will build robust, scalable interfaces capable of rendering insights from millions of documents with sub-second latency. By bridging the gap between complex AI services and the end-user, you will ensure that massive-scale data is transformed into performant, intuitive, and highly responsive web applications.
• Partner with cross-functional, distributed teams to evaluate and adopt emerging technologies, while leading the seamless integration and optimization of intelligent features and high-impact workflows across the platform
• Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who you are

Core Qualifications

• 8+ years of experience building complex, data-intensive full-stack systems, with 5+ years specifically scaling production-grade services using Node.js, GraphQL, and modern JavaScript/TypeScript ecosystems.
• Deep expertise in React and TypeScript; a proven ability to codify performance best practices, navigate complex architectural trade-offs, and drive code-level improvements.
• Proven success in designing large-scale asynchronous systems using streaming, queuing, and caching strategies, supported by robust observability (logging, metrics, tracing).
• Strong proficiency with SQL/NoSQL (e.g., DynamoDB, Elasticsearch, Vespa) and cloud-native development within AWS or GCP.
• Working knowledge of Python or Java/Spring.
• Passion for AI-assisted development (e.g., Cursor, Claude) 
• Exceptional communicator able to articulate complex technical concepts and influence engineering direction across multiple teams without direct authority.
• Prior experience at global technology companies or high-growth product organizations with a high-bar engineering culture.

Nice to have

• Proficient in modern DevOps/MLOps, including CI/CD, IaC, and automated testing frameworks.
• Hands-on experience with Docker and Kubernetes for containerized application delivery.

Practical experience deploying LLM applications, agentic frameworks, or scalable AI infrastructure.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

About the Role:

We are seeking a visionary and hands-on Principal AI Engineer to be the foundational pillar of our strategy in the Content portfolio. You will be the catalyst who injects deep, modern AI expertise into our product portfolio. Your mission will be to research, architect, and pioneer the solutions that will process and extract intelligent insights from millions of unstructured documents and multi-media files every single day.

This is a unique "founding engineer" opportunity to shape the future of AI within our company. You will be the primary AI/ML authority, responsible for identifying and implementing state-of-the-art techniques for document classification, entity extraction, image search, and more. If you are a seasoned engineer who thrives on solving massive-scale data challenges and wants to build a center of excellence from the ground up, this role is for you.

What You’ll Do:

• Spearhead AI Innovation: Act as the chief technical authority on AI, you will research, evaluate, and prototype cutting-edge solutions using Large Language Models (LLMs), Computer Vision, and other machine learning techniques to solve our most complex data extraction challenges.
• Architect for Scale: Design and build robust, highly scalable, and cost-effective AI services and data processing pipelines. Your architecture will be the backbone for processing millions of documents daily with high reliability and throughput.
• Tackle Real-World AI Challenges: Go beyond theory to systematically solve the practical problems of production AI. This includes managing LLM latency and variance, developing sophisticated prompt engineering strategies, and building fault-tolerant, defensive systems that perform consistently.
• Be a Force Multiplier: Act as the key technical mentor and thought leader for our large engineering team and drive some mission-critical initiatives to production

Who You Are:

Core Qualifications

• 12+ years of professional software engineering experience, with a proven track record of building complex, data-intensive, backend systems.
• Deep expertise (5+ years) in building and scaling production-grade services using modern backend frameworks such as FastAPI, Django, Sanic, Spring Boot or similar.
• Significant, hands-on experience (3+ years) in the complete lifecycle of AI/ML models: from experimentation and prototyping to deploying, monitoring, and iterating on them in a high-volume cloud environment.
• Mastery in designing large-scale distributed systems, demonstrating strong knowledge of asynchronous patterns, streaming/queuing/caching strategies, and robust observability (logging, metrics, tracing).
• Exceptional communication and leadership skills. You can articulate complex technical concepts to diverse audiences and have the ability to influence engineering direction across multiple teams without direct authority.

Nice to have

• Proficiency with modern DevOps and MLOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing frameworks.
• Hands-on experience with containerization and orchestration technologies, particularly Docker and Kubernetes.

Build and operate the production backbone that takes models from Applied Sciences (AS) and delivers reliable, low-latency ML services across Tekion’s DMS, CRM, Digital Retail, Service, Payments, and enterprise products. You’ll own pipelines, microservices, CI/CD, observability, and runtime reliability—working hand-in-hand with Applied Sciences and Product to turn ideas into measurable dealer and consumer impact. 

Why this Role Matters 

• Accelerate the rollout of LLM-powered and agent-driven features across Tekion products. 

• Enable agentic workflows that automate, reason, and interact on behalf of users and internal stakeholders. 

• Operationalize secure, compliant, and explainable LLM and agentic services at scale. 

• Convert Applied Sciences models into scalable, compliant, cost‑efficient production services. 

• Standardize how models are trained, validated, deployed, and monitored across Tekion products. 

• Power real-time, context-aware experiences by integrating batch/stream features, graph context, and online inference. 

What You’ll Do 

• Turn Applied Sciences prototype models (tabular, NLP/LLM, recommendation, forecasting) into fast, reliable services with well-defined API contracts. 

• Integrate with the LLM Gateway/MCP, prompt/config versioning. 

• Build and orchestrate CI/CD pipelines. 

• Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality. 

• Collaborate with data scientists, data engineers, product managers, and architects to design enterprise systems. 

• Monitor, detect, and mitigate risks unique to LLMs and agentic systems. 

• Implement prompt management: versioning, A/B testing, guardrails, and dynamic orchestration based on feedback and metrics. 

• Design batch/stream pipelines (Airflow/Kubeflow, Spark/Flink, Kafka) and online features linked to our domain graph. 

• Build inference microservices (REST/gRPC) with schema versioning, structured outputs, and stringent p95 latency targets. 

• Manage the model/feature lifecycle: feature store strategy, model/agent registry, versioning, and lineage. 

• Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking. 

• Ensure real-time reliability: autoscaling, caching, circuit breakers, retries/fallbacks, and graceful degradation. 

• Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path. 

Desired Skills and Experience 

• 6+ years in ML engineering/MLOps or backend/platform engineering with production ML. 

• Experience with LLMs, retrieval systems, vector stores, and graph/knowledge stores. 

• Strong software engineering fundamentals: Python plus one of Java/Go/Scala; API design; concurrency; testing. 

• Hands-on with orchestration frameworks and libraries (LangChain, LlamaIndex, OpenAI Function Calling, AgentKit, etc.). 

• Knowledge of agent architectures (reactive, planning, retrieval-augmented agents), and safe execution patterns. 

• Pipelines and data: Airflow/Kubeflow or similar; Spark/Flink; Kafka/Kinesis; strong data quality practices. 

• Microservices and runtime: Docker/Kubernetes, service meshes, REST/gRPC; performance and reliability engineering. 

• Model ops: experiment tracking, registries (e.g., MLflow), feature stores, A/B and shadow testing, drift detection. 

• Observability: OpenTelemetry/Prometheus/Grafana; debugging latency, tail behavior, and memory/CPU hotspots. 

• Cloud: AWS preferred (IAM, ECS/EKS, S3, RDS/DynamoDB, Step Functions/Lambda), with cost optimization experience. 

• Security/compliance: secrets management, RBAC/ABAC, PII handling, auditability. 

Preferred Mindset 

• Product-oriented: You measure success by dealer and consumer outcomes, not just technical metrics. 
• Reliability- and safety-first: You move fast with guardrails, rollbacks, and clear SLOs. 
• Systems thinker: You design for multi-tenant scale, portability, and cost efficiency
• Collaborative: You translate between Applied Sciences, Product, and the Data & AI Platform; you document and teach. 

Senior Software Engineer  -  Senior Machine Learning Platform

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 5 - 7 years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

• Documentation and teaching: you make complex systems understandable; you uplevel teams. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Staff Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Senior Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Senior Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 5+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.