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. 

Come join our Engineering team

Our Software Engineering team is dedicated to building the world’s most predictive, inclusive, and fair interviewing products for our clients and technical candidates alike.

What you will do

As a Software Engineer (SWE3) at Karat, you'll build product features that directly improve how engineers are interviewed and hired. You'll take full ownership of projects within your team's scope, driving them from design through implementation, while collaborating closely with engineers, product managers, and designers to deliver high-quality software.

This position requires a schedule that overlaps with U.S. business hours.

• Embrace AI-assisted development as a core part of your workflow; stay current with emerging techniques and contribute to evolving team practices.
• Design and build features across the full stack using a variety of programming languages, testing frameworks, and development tools.
• Write clean, scalable services, components, and APIs; make sound architectural decisions within your workstream.
• Own and deliver projects independently from design to release, including those with meaningful ambiguity and architectural complexity, with high-quality code and minimal defects.
• Take strong ownership of all code you touch, proactively improving quality rather than just meeting the immediate requirement.
• Collaborate with a cross-functional team of Analysts, Data Scientists, Designers, Product Managers, and Engineers to define and deliver product features.
• Champion engineering best practices, including testing strategy, performance optimization, and technical debt management.

The experience you will bring

• 5+ years of professional (post-intern) experience designing and shipping web applications and distributed systems to production
• Proficiency in modern programming languages (Ruby, Python, React, TypeScript/JavaScript) with solid command of web frameworks and design patterns across the stack
• Experience with system architecture, database design, and API development (REST and/or GraphQL)
• Experience with cloud infrastructure, DevOps practices, and scalable deployment technologies (AWS, GCP, or Azure)
• Strong analytical and problem-solving skills; ability to navigate technical complexity and articulate trade-offs clearly
• Excellent written and verbal communication skills in English; proven ability to collaborate effectively with cross-functional stakeholders
• Interest in technical interviewing, talent assessment, or edtech is a strong plus

This position is only available to candidates residing in Bengaluru (formerly known as Bangalore). While our team operates 100% remotely, we are currently limiting hiring to this specific location. Applications from other cities in India will not be considered at this time.

Applicants, please note: submissions not 100% in English will not be considered.

Come join our Engineering team

Our Software Engineering team is dedicated to building the world’s most predictive, inclusive, and fair interviewing products for our clients and technical candidates alike.

What you will do

As a Staff Software Engineer at Karat, you'll lead the most complex, cross-team technical initiatives at the company and shape the direction of our engineering organization. You'll drive significant architectural improvements to our platform, set the technical vision for the systems your teams depend on, and bring Karat's technical voice into the room with clients, building trust, shaping product direction, and ensuring our most important relationships are grounded in deep technical credibility. Your impact will be felt not just in the code you ship, but in how the entire engineering organization builds.

This position requires a schedule that overlaps with U.S. business hours.

• Embrace AI-assisted development as a core part of your workflow; lead the team's thinking on how emerging techniques should shape Karat's engineering practices at scale.
• Lead the design and delivery of complex, cross-team technical initiatives, navigating ambiguity, aligning stakeholders, and driving projects through to production even when product direction is unclear.
• Own significant areas of Karat's technical stack, proactively identifying and proposing improvements that meaningfully advance developer experience and end-user outcomes.
• Design significant architectural changes to the platform, evaluating trade-offs at scale and ensuring decisions serve both current needs and long-term organizational health.
• Bring Karat's technical voice into the room with clients, building trust, shaping product direction, and ensuring our most important relationships are grounded in deep technical credibility.
• Mentor and elevate engineers across levels, contributing to a culture of technical excellence and continuous improvement.
• Champion engineering best practices across the organization, including testing strategy, performance optimization, and technical debt management.

The experience you will bring

• 10+ years of post-internship professional experience leading the architecture and delivery of large-scale, complex web applications and distributed systems in production; a demonstrated record of organizational-level technical impact
• Deep expertise in modern programming languages (Ruby, Python, React, TypeScript/JavaScript) with mastery of web frameworks, design patterns, and system design at scale
• Expert-level experience with microservices architecture, database optimization, and API design at scale (REST and GraphQL)
• Deep experience with cloud infrastructure, DevOps practices, and scalable deployment technologies (AWS, GCP, or Azure)
• Proven technical leadership across teams and initiatives, with a track record of driving organizational-level technical improvements
• Comfort engaging directly with clients or external stakeholders, with the ability to represent complex technical work clearly and build trust in a client-facing setting
• Interest in technical interviewing, talent assessment, or edtech is a strong plus

This position is only available to candidates residing in Bengaluru (formerly known as Bangalore). While our team operates 100% remotely, we are currently limiting hiring to this specific location. Applications from other cities in India will not be considered at this time.

Applicants, please note: submissions not 100% in English will not be considered.

Come join our Engineering team

Our Software Engineering team is dedicated to building the world’s most predictive, inclusive, and fair interviewing products for our clients and technical candidates alike.

What you will do

As a Senior Software Engineer at Karat, you'll own complex, technically demanding projects on our flagship interviewing platform and drive them end-to-end. You'll make significant architectural decisions, actively improve technical quality across the team's codebase beyond your own lane, and collaborate closely with engineering leadership to raise the bar on how we build.

This position requires a schedule that overlaps with U.S. business hours.

• Embrace AI-assisted development as a core part of your workflow; stay current with emerging techniques and help evolve the team's practices as the field advances rapidly.
• Design and build sophisticated web applications across the full stack; own significant architectural decisions that ensure long-term maintainability and performance.
• Own and deliver complex, heavily ambiguous projects from design to release, independently resolving significant architectural questions and seeing work through to production.
• Proactively identify and address technical quality issues beyond your immediate project scope, looking across the team's systems to reduce risk and improve reliability.
• Mentor junior engineers, elevating the team's overall capability through knowledge sharing, code reviews, and hands-on guidance.
• Collaborate with a cross-functional team of Analysts, Data Scientists, Designers, Product Managers, and Engineers to define and deliver product features.
• Champion engineering best practices, including testing strategy, performance optimization, and technical debt management.

The experience you will bring

• 7+ years of post-internship professional experience owning and delivering complex, full-stack web applications and distributed systems end-to-end in production
• Deep expertise in modern programming languages (Ruby, Python, React, TypeScript/JavaScript) with strong command of web frameworks and design patterns across the stack
• Strong experience with system architecture, microservices design, database optimization, and API development (REST and GraphQL)
• Hands-on experience with cloud infrastructure, DevOps practices, and scalable deployment technologies (AWS, GCP, or Azure)
• Demonstrated technical leadership, including mentoring teammates and driving technical initiatives
• Excellent written and verbal communication skills in English; proven ability to work with diverse stakeholders and translate technical concepts for non-technical audiences
• Interest in technical interviewing, talent assessment, or edtech is a strong plus

This position is only available to candidates residing in Bengaluru (formerly known as Bangalore). While our team operates 100% remotely, we are currently limiting hiring to this specific location. Applications from other cities in India will not be considered at this time.

Applicants, please note: submissions not 100% in English will not be considered.

Senior Software Engineer:

Role summary Build, evolve, and operate backend services at scale for ZoomInfo. You’ll work primarily with Node.js/TypeScript (NestJS preferred), design robust REST/GraphQL APIs, optimize MongoDB/Redis, and deploy on cloud (GCP preferred or AWS) with a strong focus on reliability, performance, security, and cost efficiency.

What you’ll do:

• Design, implement, and own microservices and REST/GraphQL APIs in Node.js/TypeScript (NestJS preferred)
• Translate product requirements into technical designs; break down work, estimate, and deliver incrementally
• Model data and optimize queries in MongoDB; implement effective caching with Redis (TTL, eviction, hot-key mitigation)
• Ship production-ready code with unit/integration tests; participate in on-call, incident response, and postmortems
• Containerize and deploy via Docker/Kubernetes; automate builds and releases with CI/CD (blue/green or canary)
• Instrument services for logs, metrics, and traces (p95/p99); continuously improve latency, reliability, and cost
• Review code, document designs, and mentor SE II/III engineers; contribute to shared standards and best practices

What you bring:

• 7+ years of software engineering experience, including 3+ years building backend services in Node.js/TypeScript
• Strong API fundamentals: versioning, pagination, authN/Z (OAuth/OIDC), and secure coding (OWASP)
• Hands-on with NestJS/Express/Fastify; familiarity with microservices patterns and event-driven workflows
• MongoDB expertise (schema design, indexing, basic sharding concepts) and Redis caching patterns
• Cloud experience on GCP (preferred) or AWS; Docker; working knowledge of Kubernetes; CI/CD with GitHub Actions/Jenkins/GitLab
• Observability skills: Datadog/OpenTelemetry/Prometheus/Grafana; confident debugging in production
• Collaboration and communication skills; bias for clean, well-tested, and well-documented code

Nice to have:

• Kafka or Pub/Sub; API Gateway/Ingress; feature flags; rate limiting and quotas
• Terraform/Helm; security tooling (SonarQube), dependency hygiene, secret management
• Performance profiling, load testing, and practical cost optimization

#LI-PM1

#LI-Hybrid

Role

We are looking for a Staff Software Engineer to join our Engineering team in a hybrid capacity in Bangalore, reporting to the Senior Director, Software Engineering. You will join the team that built the world’s largest cloud security platform from the ground up. Bring your vision and passion to our team of cloud architects and software engineers who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy.

What you’ll do (Role Expectations)

• Lead the engineering effort for the development and maintenance of the Zscaler Zero-Trust Cloud User Interface

• Work closely with the UI design team to implement intuitive and accessible user interfaces, leveraging UX best practices and a component library

• Collaborate with the product team to define and implement functional requirements that align with business goals

• Develop high-quality, maintainable code with thorough unit and end-to-end (E2E) tests using frameworks such as Jest, Cypress, or Playwright

• Advocate for UI platform priorities, ensuring alignment with long-term architectural goals and business needs

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful

• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution

• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact

• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust

• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose

What We’re Looking for (Minimum Qualifications)

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

• 6+ years of professional experience as a front-end engineer, with at least 5 years of experience specifically in React

• Extensive experience with JavaScript and developing UI components using React

• Strong understanding of UI/UX design principles and implementing efficient, scalable GraphQL and REST APIs

• Proven ability to address key UI concerns such as scalability, performance, and security to maintain a high-quality user experience

What Will Make You Stand Out (Preferred Qualifications)

• Strong understanding of front-end build tools, package managers, monorepos, and version control systems such as Nx, npm, and Git

• Familiarity with containerization and Kubernetes

• Understanding of AWS services including Cloudfront, EC2, and S3 and their application in secure, scalable, and highly available UI deployments

#LI-Hybrid #LI-GL2

An overview of this role

As an AI Engineer at GitLab, you'll help build the foundation for GitLab's transformation into an AI-first company. Reporting to the Director, Enterprise AI, you'll be a hands-on technical leader responsible for delivering internal AI-powered solutions that drive measurable business outcomes.

Building fast matters, but it's not enough on its own. This role starts with understanding the real problem: mapping how work moves across teams, tools, and handoffs, identifying the true constraint, and validating whether AI is the right solution before you begin development. From there, you'll take ownership from discovery through deployment, combining strong engineering skills with systems thinking and business understanding.

Your initial focus will span Sales, Marketing, and Customer Support, where you will embed AI solutions into key systems and workflows. This role offers the opportunity to shape how GitLab team members work, improve flow across the organization, and help advance our mission in a remote, asynchronous, and values-driven environment.

What you'll do

• Diagnose business problems before building solutions. Map workflows, identify constraints, and confirm whether AI is the right intervention. Be prepared to say "this doesn't need AI" when that's the honest answer.
• Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration.
• Design, develop, and ship AI-powered solutions quickly, delivering working prototypes in days, not months, with a focus on practical outcomes and measurable business value.
• Improve organizational flow by building solutions that reduce bottlenecks, shorten lead times, and increase throughput. Measure success using flow metrics alongside adoption and ROI.
• Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms, including GitLab Duo Agent Platform, where appropriate. The right tool wins, whether that's custom code, a platform, or a well-crafted prompt.
• Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible, feeding real-world usage insights back to R&D.
• Partner closely with stakeholders across functions to understand the real constraints. Ask the right questions, bridge technical and non-technical perspectives, and align on outcomes before jumping to solutions.
• Define and track success through business metrics, flow metrics, and feedback loops that make performance visible and actionable.
• Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations that help the team scale its impact.

What you'll bring

• A Technologist at Heart - Genuinely invested in technology, the foundational and the cutting-edge in equal measure. You're as energised by a well-designed API integration as you are by the latest foundation model release. You reach for the simplest solution that solves the problem well, rather than forcing new technology when proven approaches would do. AI is a powerful part of your toolkit, but it sits on top of solid engineering fundamentals, not in place of them.
• Competent, Confident Coding Skills - You can build working solutions end-to-end, write clean and maintainable code, and debug effectively. Whether your skills were honed in a traditional engineering role, through building automations, or shipping side projects, what matters is that you can deliver production-quality work independently.
• AI & LLM Technical Depth - Strong proficiency in at least one modern scripting language (Python, JavaScript/TypeScript, or similar) and a solid understanding of REST APIs, GraphQL, and integration patterns. Deep, practical experience with modern AI technologies, specifically: Prompt engineering as a core discipline: designing effective system prompts, managing context windows, structuring multi-turn interactions, evaluating output quality, and iterating systematically on prompt design.Model selection and cost-performance trade-offs: understanding when a smaller fine-tuned model outperforms a general-purpose large one, when RAG is the right architecture versus expanding the context window, and how to make principled decisions about capability versus cost.
• Agentic architecture patterns: tool use, multi-agent orchestration, human-in-the-loop designs, guardrails, evaluation frameworks, and production-grade reliability patterns.Practical fluency across the LLM ecosystem: hands-on experience with models from Anthropic, OpenAI, open-source alternatives, and the judgment to know which to reach for and when.
• AI Safety & Risk Awareness - You think critically about how the solutions you build could be exploited, misused, or produce unintended consequences. You know how to design appropriate guardrails (input validation, output filtering, access controls, prompt injection defences, and data leakage prevention) and you treat these as first-class engineering concerns.
• Systems Thinking & Diagnostic Rigour - The ability to look at a complex process and see the constraint. Comfortable mapping how work flows end-to-end, identifying bottlenecks, and tracing problems to root causes before proposing solutions. You instinctively ask "what's actually blocking flow here?" before asking "what model should I use?"Business System Expertise - Familiarity with the landscape of enterprise business systems, CRM (Salesforce), marketing automation (Marketo), support platforms (Zendesk), integration and orchestration tools (Workato), AI platforms (Relevance AI), and enterprise search and knowledge tools (Glean). You don't need deep experience with all of these, but to understand what they do, how they fit together, and be willing to build with and across them. A strong understanding of enterprise data models and workflows is essential.
• Broad Functional Understanding - Ability to have meaningful conversations with stakeholders across diverse domains and quickly understand their unique needs.
• End-to-End Ownership - Track record of owning complex initiatives from discovery through delivery. Comfortable operating with ambiguity and driving to measurable outcomes independently.
• Product Mindset - Ability to scope MVPs, prioritise ruthlessly, and deliver iteratively. In addition, consider adoption, user experience, and business outcomes.

Preferred Qualifications

• Experience with GitLab platform and CI/CD workflows
• Background in consulting, solutions engineering, or customer-facing technical roles
• Familiarity with value stream mapping, flow metrics, or Theory of Constraints thinking
• Experience with low-code/no-code orchestration tools (n8n, Make, Workato) alongside custom development
• Previous startup or high-growth company experience
• Experience mentoring or leading technical projects with junior engineers

About the team

You will join the Enterprise Technology & AI team. We're the backbone of the organisation, driving transformation in how GitLab team members make decisions, operate at scale, and deliver results for our customers.

We believe the best AI solutions start with understanding the system, not the technology. We value people who think in constraints and flow, who build with conviction, and who never stop learning. We work in an all-remote, asynchronous setting, guided by GitLab's values of collaboration, results, efficiency, diversity, inclusion and belonging, iteration, and transparency.

Role: Senior Software Engineer / Principal Software Engineer            

Office Location: Bangalore

We write our code leveraging the Microsoft stack (ReactJS, .NET Core, MS SQL Server , PostgreSQL, AWS).  We’re relentless, curious, and doing the right thing is a tenet of the team’s approach to solving business problems. We are flexible and collaborative. We all enjoy our work and helping one another is baked into our operating DNA. We believe in Agile software development principles. We are huge proponents of SOLID principles.

The Software Engineer at Analytical Wizards:

• Has  5+ years of experience in a fast-paced Agile software development environment
• Ensures software is built, according to business and technical specifications, on top of an error-free and high-performing platform
• Innovates!
• Performs code reviews and QA on team members’ work items
• Participates in Agile ceremonies
• Mentors more junior members of the team
• Is always thinking of better ways to do something
• Isn’t afraid to fail
• Cares deeply about quality
• Can deliver high-quality software with minimal supervision

Required Skills:

• Experience of 5+ years experience in C#, .NET & .NET Core (5 & above)
• Solid computer science fundamentals - OOP concepts, SOLID principles & design patterns
• Experience with any relational databases (MS SQL / MySQL /Postgres)
• Experience working with public cloud like Azure/AWS/GCP (AWS is preferred)
• Experience with containerization using Docker & microservices
• Experience developing RESTful APIs
• Understanding of various types of testing (unit, system, integration, performance)
• General familiarity with cloud computing and serverless architectures

Preferred Skills:

• Experience in front-end development (React, JavaScript, KendoUI)
• Exposure to GraphQL (HotChocloate)
• Exposure to DataDog or similar logging & monitoring tool
• Familiarity with NoSQL databases (MongoDB /DocumentDB)

Why we love Analytical Wizards, and why you will too!

• Industry leading products
• Work hard, and have fun doing it
• Incredibly fast growth means limitless opportunity
• Flexible and dynamic culture
• Work alongside some of the most talented and dedicated teammates
• A collaborative and friendly culture with very high employee engagement

About Company

Company Name: AnalyticalWizards Services Pvt. Ltd.

Profile: A leading, high growth Analytics Software Development company developing products that touch and positively impact human lives across the globe. We are headquartered in New Jersey and have a software development and delivery center in Bangalore. Our work is mainly focused on Healthcare Industry. We develop core data science products that help our clients draw unique insights from their big data and achieve their business goals. We use advanced algorithms in the space of artificial intelligence and machine learning. Our technology-based software products are being used by the top pharma and biotechnology companies of the world. We have been recognized twice as one of fastest growing private companies of USA.

Work Culture: Employee-friendly, collaborative, innovative, fast-paced, and conducive to learning

Company Address: AnalyticalWizards Services Private Limited, Fortune Summit Business Park, Ground Floor, Hosur Road, Sector 6, HSR Layout, Roopena Agrahara, Bangalore - 560068

Industry: Software Development and Data Science

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:

As a Forward Deployed Engineer at DevRev, you will work closely with our pre- and post-sales Customer Experience team by developing solutions over the core platform via applications written in TypeScript, JavaScript, Python, etc. One of the key functions of this role is, building the Knowledge Graph that includes integration of DevRev with other SaaS and non-SaaS systems through webhooks and APIs and/ or real-time communication architectures. You will be expected to employ your creativity and expertise to ideate and shape how AI, analytics and workflows are used in customers' processes.

What You'll Do:

• Customer-facing: 30% working directly with customers.
• Coding & Integration: 70-80% hands-on technical implementation
• Build & Deploy Solutions: Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows.
• Integrate Systems: Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow.
• Optimize AI Performance: Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy and user experience.
• Own Data Insights: Write SQL queries, perform data analysis, and build dashboards to surface insights that drive customer decision-making.
• Prototype & Iterate: Develop rapid proofs-of-concept, conduct live technical demos, and refine solutions based on customer and stakeholder feedback.
• Lead Cross-functional Collaboration: Maintain constant communication loops with customers, engineering, product, customer success, support, and revenue teams to ensure alignment.
• Guide Technical Adoption: Learn and master new tools, then guide customers through critical workflows like code repository integrations and advanced configurations.
• Travel Ready: Willingness to travel up to 30% for on-site implementations, technical workshops, and customer engagements.

What You Bring:

• Experience: 5+ years in software development, systems integration, or platform engineering. Customer-facing experience is a plus.
• Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• Coding Skills: Strong proficiency in TypeScript/JavaScript, Python, data structures and algorithms. (Nice to have: Go)
• Applied AI Knowledge: Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
• Integration Expertise: Deep experience with large-scale data synchronization (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures.
• Cloud & Deployment: Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
• Data Transformation: Skilled in data mapping, schema alignment, and working with heterogeneous systems. Understanding of data modeling and graph data structures.
• Observability: Experience implementing clear logging, actionable error surfacing, and telemetry to support faster debugging and issue resolution.
• Context-Aware Systems: Familiarity with Model Context Programming (MCP) for building adaptive, context-aware integrations.
• Problem-Solving: Strong track record triaging and unblocking both technical and non-technical blockers to keep projects moving forward.
• Documentation: Experience writing concise, well-structured documentation that supports long-term team understanding and seamless onboarding.
• Communication: Strong written and verbal skills to articulate technical concepts to engineers, product teams, and business stakeholders.
  
  As part of our hiring process, shortlisted candidates will undergo a Background Verification (BGV). By applying, you consent to sharing personal information required for this process. Any offer made will be subject to successful completion of the BGV.

Toast is building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: running the businesses they love. We’ve grown into a leading hospitality software company in the U.S., and are now entering our next phase of growth—one defined by scale, complexity, and a new class of enterprise customers.

Every restaurant is unique, and a restaurant’s menu expresses its individual brand and product offerings. Inside a Toast restaurant, the definition of the menu becomes the common language between guests, servers, and the kitchen. In our digital ordering products, a great menu serves as both a billboard and a roadmap to an excellent dining experience. It is the central hub for restaurant configuration– it determines what guests can order, how the dishes are presented and priced in different contexts, where they are routed for fulfillment and how they are coursed, how they are prepared, whether the ingredients are still available, and how they are classified for reporting. A menu is always evolving: kitchens create new dishes, managers experiment with pricing and presentation, and staff optimize the menu for restaurant operations. 

We create products to satisfy the vast breadth of our restaurants, from single-location coffee shops to complex enterprise brands with thousands of locations. We offer an extremely powerful and configurable menu platform, and our team exists to ensure that this flexibility can be managed effectively at any scale. This includes feature-rich menu data models, APIs for both first and third party integrations (eg: DoorDash and other ordering partners), and the user experiences for configuring menus that meet a vast variety of needs, from complex customer segments (eg: Pizza shops) to our evolving Retail platform. 

We are looking for a visionary engineer who is motivated by these challenges and eager to transform our menus architecture to meet the dynamic needs of our customers and our rapidly growing business. As a Principal Software Engineer on the Menus team, you will take ownership of this essential function, making strategic technical decisions that enhance our capabilities and ensure scalability. You will have the opportunity to make a huge impact in a critical space. Your leadership will drive excellence within the team and influence our broader engineering community, setting new standards and contributing to our collective success.

About this roll* (Responsibilities) 

• Lead the evolution of our Menus architecture and data models, delivering scalable solutions that have significant business impact.
• Define and implement frameworks and processes that guarantee the quality, resilience, and scalability of our user experiences and API platform.
• Develop and execute technical strategies to solve complex business challenges, leveraging data-driven decisions to prioritize impactful changes.
• Establish guiding technical and delivery principles that influence engineering practices across the broader engineering organization.
• Mentor and guide engineers, fostering a culture of continuous improvement, inclusivity, and engineering excellence.
• Build and maintain strong partnerships across lines of business, aligning technical solutions with strategic objectives.

Do you have the right ingredients*? (Requirements)

• Minimum education: BE or B.Tech in a technology-related field
• 10+ years of experience in software engineering, with a strong background in back-end development using Java, Kotlin, or other object-oriented language
• Proficient with modern API standards and technologies (e.g. REST, GraphQL)
• Proficient with relational databases and alternative data stores
• Experience with distributed systems, enterprise messaging systems, and/or microservices
• Demonstrated ability to deliver high-impact, scalable solutions in complex, multi-product environments.
• Strong leadership and mentoring skills, with a track record of guiding teams through architectural transformations.
• Excellent communication skills, with the ability to articulate complex technical concepts to diverse audiences.
• Passionate about driving innovation and continuously improving engineering practices.

Role

We’re looking for a Full Stack Software Engineer to join our team. This role is based in Bangalore, India, reporting to the Sr. Manager of Software Engineering within the Risk360 department You will join the team that built the world’s largest cloud security platform from the ground up to help organizations worldwide harness speed and agility with a cloud-first strategy. In this role, you will be a key contributor to our multitenant architecture, enabling the delivery of innovative services to over 15 million users across 185 countries.

What you’ll do (Role Expectations)

• Develop product features related to data transformations, enrichment, analytics, and user-facing dashboards
• Design and implement intuitive, performant web applications using ReactJS for data visualization and user interaction
• Build and maintain data processing pipelines to handle data ingestion, transformation, and analysis for risk quantification
• Establish monitoring mechanisms to track data platform performance and health while defining maintenance procedures
• Collaborate closely with UX/UI designers and backend engineers to deliver seamless end-to-end solutions

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• 3+ years of experience in software development for enterprise solutions, including web-based applications
• 1+ years of experience in ReactJS or similar modern JavaScript frameworks, including component-based architecture and state management
• Solid experience in Core Java, Concurrency, Distributed Computing, and proficiency in SQL
• Exposure to Test Driven Development (TDD) using frameworks such as JUnit, REST Assured, TestNG, or Jest
• Experience with HTML5, CSS3, JavaScript/ES6+, and building responsive interfaces

What Will Make You Stand Out (Preferred Qualifications)

• Experience developing scalable web applications handling large datasets efficiently and working knowledge of GraphQL
• Expertise in state management frameworks like Redux and performance optimization including tuning JVM
• Understanding of security compliance frameworks, statistics, and machine learning

#LI-Hybrid #LI-AN4

As a Senior Software Engineer, you will get to explore and work with cutting-edge technologies and a large and rich data set. If you like working on tough problems, whether that's building systems that handle millions of customer requests a day or how to make sense of over a billion pieces of potentially correlated data, ZoomInfo is the right place for you.

The ideal candidate is a seasoned engineer with a deep understanding of modern server-side technologies and distributed systems. They possess strong skills in building modular, maintainable, and scalable backend services with an emphasis on performance, reliability, and security. The candidate should have a keen eye for detail, a passion for building robust systems, and the ability to collaborate effectively within cross-functional teams.

What You'll do:

• Design, develop, and maintain high-performance backend services capable of handling millions of requests daily.
• Collaborate with other team members and stakeholders to contribute to the design and evolution of scalable applications, ensuring scalability, reliability and performance
• Work with TypeScript, NestJS, and Node.js to build and optimize backend applications.
• Work with RESTful APIs, GraphQL and integrate with external services, ensuring data consistency, robustness and security
• Manage and optimize data storage solutions using MongoDB, Redis ensuring efficient and reliable data access.
• Integrate with Confluent Cloud to manage data streaming and real-time processing pipelines.
• Conduct thorough code reviews to maintain high-quality standards across the codebase.
• Collaborate with other engineers to solve complex and intriguing problems.
• Stay up-to-date with the latest backend technologies and industry trends.
• Contribute to the continuous improvement of our technology stack and development processes.

What you bring:

• 8+ years of industry experience with a B.S. in Computer Science or equivalent.
• Strong experience in backend development with TypeScript, NestJS, Node.js and java.
• 5+ years of experience with JavaScript/TypeScript and Node.js.
• Proficiency in working with MongoDB and managing large-scale databases.
• Experience with Confluent Cloud or similar data streaming platforms is a plus.
• Familiarity with CI/CD tools for automating builds, testing, and deployments (e.g., Jenkins).
• Proficiency in working with RESTful APIs and GraphQL
• Must be able to work independently and deliver excellent results in short timelines
• Technically lead and mentor juniors in the team, and drive planning and execution of work
• Experience with containerization and orchestration tools (Docker, Kubernetes)
• Strong problem-solving and debugging skills with experience in high-traffic applications
• Experience with backend technologies (Node.js, Python, or Java) and microservices architecture
• Excellent communication and collaboration skills
• Ability to thrive in a dynamic, fast-paced environment

#LI-SG2

#LI-Hybrid

Narvar is growing! We are looking for Senior Software Engineers that enjoy working on both APIs and UIs. In this role, you will build products that power the post-purchase experience for the biggest brands in the retail industry. As a Fullstack Software Engineer, you will have a direct impact on our customer-facing products and work with modern technologies like NodeJS, React, PostgreSQL and GraphQL to ship complex features that drive millions of views.

Day-to-day

• Implement new product features & support/ extend existing ones
• Build REST and GraphQL APIs that support a high volume of traffic
• Build frontend platform components leveraged across our internal and external products
• Contribute to our overall architecture and development experience partnering with other senior engineers

What we're looking for

• You have a BS/MS in computer science, information systems, or equivalent
• You have 7+ years of experience building reliable, scalable, and high-quality systems
• Experience with a frontend framework(s), such as React, Svelte Angular, Vue or Ember
• Experience building well-designed software with NodeJS, React and PostgreSQL
• Experience developing consumer facing applications consuming various APIs from a microservice backend system
• Experience defining REST or GraphQL APIs for new features
• Knowledge of full development life cycle and computer science fundamentals
• Experience with mentoring other engineers
• Previous startup experience strongly preferred
• Proficiency in utilising AI tools like Claude, Cursor, Copilot etc

Bonus point

• Experience working with Java, SpringBoot or Golang knowledge is a plus point

Why Narvar?

We're on a mission to simplify the everyday lives of consumers. Post-purchase is a critical phase of the customer journey. That's why we created Narvar - a platform focused on driving customer loyalty through seamless post-purchase experiences that allow retailers to retain, engage, and delight customers. If you've ever bought something online, there's a good chance you've used our platform!

From the hottest new direct-to-consumer companies to retail’s most renowned brands, Narvar works with GameStop, Neiman Marcus, Sonos, Nike, and 1300+ other brands. With hubs in San Francisco, Atlanta, London, and Bangalore, we've served over 125 million consumers worldwide across 10+ billion interactions, 38 countries, and 55 languages.

Pioneering the post-purchase movement means navigating into the unknown. Our team thrives on this sense of adventure while nurturing a mindset of innovation. We're a home for big hearts and we leave our egos at the door. We work hard but we always make time to celebrate professional wins, baby showers, birthday parties, and everything in between.

We are an equal-opportunity employer and value 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.

#LI-PR1

#LI-Hybrid

Role Overview

As a Staff Solutions Engineer, you will play a strategic, hands-on role in transforming JazzX’s AGI platform into scalable, high-impact solutions for enterprise customers. With your deep technical expertise and leadership, you’ll drive the design, development, and deployment of LLM-powered applications across complex client environments.

You will:

• Lead the integration of LLM features, vector search pipelines, and agentic workflows into production systems.
• Partner with solution architects, product managers, and customer success teams across the full solution lifecycle—from discovery through deployment and optimization.
• Influence core platform enhancements by contributing real-world learnings and reusable components.
• Set the technical bar through design leadership, mentoring, and rigorous engineering practices.

Key Responsibilities

Solution Architecture & Implementation

• Architect and implement end-to-end AGI solutions, including retrieval-augmented generation (RAG), tool-using agents, and LLM orchestration patterns.
• Design and integrate secure data pipelines, APIs, and authorization layers tailored to customer environments.
• Make high-impact, component-level design decisions, balancing performance, maintainability, and customer goals.

Delivery Leadership

• Own delivery of proof-of-concepts, pilots, and scalable production rollouts in agile settings.
• Ensure production readiness through observability (logs, metrics, tracing) and contribute to incident response/on-call rotations as needed.

Collaboration & Enablement

• Work closely with research and product teams to test and validate emerging LLM techniques in customer contexts.
• Serve as a technical escalation point for customer implementations, proactively identifying and resolving complex issues.
• Mentor junior engineers and contribute to internal best practices through code reviews, demos, and documentation.

Innovation & Thought Leadership

• Evaluate and pilot emerging frameworks (e.g., AutoGen, LangGraph, WASM inference engines) and contribute reusable assets to the internal platform.
• Shape JazzX’s field engineering playbook by sharing insights, reusable templates, and domain-specific solutions.

Qualifications

Must-Have

• 8+ years of experience in professional software engineering, with at least 3+ years working on ML, data, or AI/LLM-centric systems.
• Strong expertise in Python (or Go/Java), with production-grade coding, testing, and CI/CD best practices.
• Proficiency in modern GenAI/LLM frameworks (e.g., LangChain, LlamaIndex, HuggingFace Transformers, PyTorch, TensorFlow) and vector databases (e.g., Pinecone, Weaviate, FAISS).
• Familiarity with integrating REST/GraphQL APIs, Kafka streams, and relational/non-relational databases.
• Excellent communication skills and the ability to work cross-functionally with engineering, product, and customer stakeholders.
• Willingness to travel up to 20% for key customer engagements.

Nice-to-Have

• Experience delivering RAG, fine-tuning, or agentic solutions in regulated industries (e.g., finance, healthcare, telecom).
• Any Certifications in cloud
• Exposure to MLOps and data engineering tools (e.g., MLflow, Kubeflow, Vertex AI, Airflow, dbt).

Attributes We Value

• Technical Leadership – You take ownership, guide architecture decisions, and raise the bar for engineering quality.
• Customer Focus – You thrive on solving real-world challenges and building trust with technical stakeholders.
• Startup Mindset – You move fast, embrace ambiguity, and iterate quickly.
• Collaboration & Mentorship – You elevate those around you through thoughtful feedback, knowledge sharing, and support.
• Mission-Driven – You’re motivated by the opportunity to shape the future of intelligent, human-centric software.

Job Title: Senior AGI Engineer – GTM Solution Delivery 

Role Overview 

As a Senior AGI Engineer you are the hands-on technical force that turns JazzX’s AGI platform into working, measurable solutions for customers. You will: 

• Build and integrate LLM-driven features, vector search pipelines, and tool-calling agents into client environments. 

• Collaborate with solution architects, product, and customer-success teams from discovery through production rollout. 

• Contribute field learnings back to the core platform, accelerating time-to-value across all deployments. 

You are as comfortable writing production-quality Python as you are debugging Helm charts, and you enjoy explaining your design decisions to both peers and client engineers. 

Key Responsibilities 

Qualifications 

Must-Have 

• 5+ years of professional software engineering experience; 2+ years working with ML or data-intensive systems. 

• Proficiency in Python (or Java/Go) with strong software-engineering fundamentals (testing, code reviews, CI/CD). 

• Hands-on experience deploying containerised services on AWS, GCP, or Azure using Kubernetes & Helm. 

• Practical knowledge of LLM / Gen-AI frameworks (LangChain, LlamaIndex, PyTorch, or TensorFlow) and vector databases. 

• Familiarity integrating REST/GraphQL APIs, streaming platforms (Kafka), and SQL/NoSQL stores. 

• Clear written and verbal communication skills; ability to collaborate with distributed teams. 

• Willingness to travel 10–20 % for key customer engagements. 

Nice-to-Have 

• Experience delivering RAG or agent-based AI solutions in regulated domains (finance, healthcare, telecom). 

• Cloud or Kubernetes certifications (AWS SA-Assoc/Pro, CKA, CKAD). 

• Exposure to MLOps stacks (Kubeflow, MLflow, Vertex AI) or data-engineering tooling (Airflow, dbt). 

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 20–30% of the time (varying by project), and flexibility is expected to accommodate key client engagement activities. 

Digital Program Developer

Position Overview

The Digital Program Developer designs, builds, and configures digital care pathways using GetWell’s content management and workflow platforms (Contentful and Total.js). This role translates clinical requirements into patient-facing digital programs by configuring content delivery, conditional logic, alerts, and multi-step workflows. You are the hands-on builder who brings care pathways to life.

Key Responsibilities

Workflow Configuration & Development (≈70%)

Care Program Build & Configuration

• Configure multi-step digital care programs in Total.js/Program Composer
• Implement conditional logic, branching scenarios, and decision trees
• Define temporal sequencing (e.g., pre- and post-procedure timelines)
• Configure alerts, escalation triggers, and severity levels
• Set up patient eligibility, enrollment, and progression logic
• Configure multi-channel communications (SMS, email, secure messaging)
• Integrate data feeds, reference dates, and enrollment criteria

Content Management (Contentful)

• Build and structure patient-facing content including:
• Educational modules and daily check-ins
• Surveys, assessments, and PROMs
• Automated messages with personalization variables
• Model structured content and reusable components
• Manage media assets (video, images, PDFs)
• Support multi-language content (English, Spanish, others as needed)

Logic & Rules Configuration

• Build scoring logic, formulas, and threshold-based alerts
• Configure skip logic, validation rules, and required fields
• Define completion criteria and program states
• Map data capture requirements and field specifications

Testing & Quality Assurance (≈30%)

Testing

• Create and execute end-to-end test plans
• Validate all logic paths, alerts, and edge cases
• Test delivery across channels and platforms
• Verify data capture, storage, and reporting accuracy
• Perform regression testing following updates or changes

Documentation

• Maintain configuration and logic documentation
• Create workflow diagrams and architecture maps
• Document business rules and decision criteria
• Support version control and change management
• Build troubleshooting and support guides

Required Qualifications

Technical & Platform Experience

• 3–5 years experience configuring complex workflows or automation platforms
  (e.g., BPM tools, CRM workflows, marketing automation platforms)
• Strong understanding of conditional logic, decision trees, and multi-step orchestration
• 2+ years experience with modern CMS platforms
  (Headless CMS preferred: Contentful, Sanity, Strapi)

Core Skills

• Strong logical and analytical thinking
• Methodical approach to testing and troubleshooting
• Comfort working with structured data and field mappings
• Ability to quickly learn new platforms and tools
• Basic understanding of APIs and system integrations

Nice to Have

• JSON/YAML configuration experience
• SQL or basic scripting (JavaScript, Python)
• Git/version control familiarity
• Jira or similar project management tools

Communication & Collaboration

• Translate clinical and business requirements into technical configurations
• Clearly communicate logic, constraints, and tradeoffs
• Document complex workflows for non-technical stakeholders
• Collaborate with product, engineering, content, implementation, and QA teams
• Present demos and walkthroughs of configured programs

Preferred Qualifications

Healthcare Experience (Helpful, Not Required)

• Familiarity with patient journeys and healthcare workflows
• Exposure to patient engagement platforms or digital health tools
• Awareness of healthcare terminology and roles
• Experience with EHR workflows (e.g., Epic, Cerner) is a plus

Advanced / Bonus Skills

• Experience with Total.js, Node.js, or Contentful
• GraphQL or HL7/FHIR exposure
• Internationalization and multi-language configuration
• Agile/Scrum team experience
• QA, testing automation, or technical documentation background

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.

Senior Software Engineer, AI Products (India)

Company Overview

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join

The Airfam Products team exists to make every Airbnb employee more productive through a unified digital headquarters experience. As part of a 13-person cross-functional team of engineers, designers, researchers, and product managers, you'll work on platforms that serve Airbnb's entire global workforce.

Our portfolio includes One Airbnb (the company's internal cultural hub with enterprise search, people profiles, and AI-powered chat), OneChat (Airbnb's enterprise AI assistant enabling secure LLM interactions), and a suite of tools that power how employees discover information, connect with colleagues, and get work done.

You'll be joining the AI for Non-Developers workstream, focused on expanding AI productivity tools to all Airbnb employees—building OneChat Agents, deep research capabilities, artifact creation tools, and task automation that make AI accessible to everyone, regardless of technical background.

The Difference You Will Make

As a Senior Software Engineer on the Airfam Products team, you'll be instrumental in building Airbnb's next generation of AI-powered employee experience platforms. Your work will be a force multiplier for the entire company—every AI feature you ship, every system you architect, and every engineer you mentor will amplify productivity across Airbnb's global workforce.

You will:

• Democratize AI by building tools that empower non-technical employees to leverage the power of LLMs
• Drive innovation by taking AI prototypes from concept to production at scale
• Shape the future of how Airbnb employees work, collaborate, and discover information

A Typical Day

• Lead the technical design and implementation of LLM-powered features for OneChat and enterprise AI tools, including RAG pipelines, AI agents, and prompt optimization
• Partner with product managers, designers, and cross-functional teams to translate user problems into AI-powered solutions that serve Airbnb's global workforce
• Develop and iterate on agentic AI capabilities, including multi-step reasoning, tool use, and context-aware decision-making
• Implement evaluation pipelines and quality systems to measure model performance, detect hallucinations, and ensure responsible AI practices
• Own production AI systems end-to-end, including deployment strategies, monitoring, alerting, and incident response
• Collaborate with the DevAI team on AirChat SDK integrations, MCP (Model Context Protocol) implementations, and Glean Action Packs
• Mentor engineers (L6-L8) through design reviews, architecture discussions, and pair programming sessions
• Stay current with the rapidly evolving GenAI landscape, evaluating new models and techniques for potential application
• Balance hands-on technical contributions with technical leadership activities

Your Expertise

Required:

• 8+ years of software engineering experience, with significant focus on building production AI/ML systems
• 2+ years of hands-on experience with Large Language Models (LLMs), including fine-tuning, prompt engineering, embeddings, and retrieval-augmented generation (RAG)
• Strong proficiency in backend technologies (TypeScript, Go, or Java)
• Strong backend and distributed systems expertise, including API design (REST, GraphQL) and cloud infrastructure (AWS, GCP, or Azure)
• Track record of shipping AI-powered products from prototype to production
• Proven ability to collaborate cross-functionally and influence without authority
• Excellent communication skills with ability to distill complex technical concepts for diverse audiences
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

Preferred:

• Master's or PhD in Computer Science, Machine Learning, or related field
• Experience building AI agents and multi-agent systems, preferably using Claude
• Experience building integrations using MCP
• Experience with containerization and orchestration (Docker, Kubernetes)
• Background in building enterprise-grade internal tools and developer productivity platforms
• Experience with frontend technologies (React, Next.js) for full-stack AI product development
• Contributions to open-source Gen AI/ML projects or publications at top venues

Your Location

This position is based in Bangalore, India with a hybrid work arrangement. You'll collaborate with teammates across global time zones, with primary alignment to Pacific Time for key meetings.

Our Commitment to Inclusion & Belonging

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

If you need assistance or a reasonable accommodation during the application and recruiting process, please contact us at: reasonableaccommodations@airbnb.com.

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. 

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.Toast is driven by building the all-in-one restaurant platform that helps restaurants operate their business, increase sales, engage guests, and keep employees happy. Toast connects employees, operations, and guests on a reliable, easy-to-use platform so restaurateurs can stay one step ahead of a rapidly evolving hospitality market. 

The mission of the International APAC team is to delight our global customers with the wide variety of Toast products. This is a relatively new team and an opportunity to help lead Toast on its journey of international expansion. As a Staff Software Engineer on the International team you will be focused on building products with a Global first mindset, working  closely with UX/PM and customers to deliver the most value that fits our customers market and culture. 

About this roll* (Responsibilities) 

• Build new products and Evolve Toast’s existing products suite to meet global market needs
• Be part of a team working collaboratively with UX, PM and other engineers building applications using modern web technologies 
• Work closely with pilot customers to ensure successful delivery and operation 
• Collaborate with teams across Toast, such as R&D, customer support and new customer onboarding
• Lead projects from discovery and development to roll out
• Mentor and coach other team members
• Promote technical excellence 
• Guiding project direction, making technical decisions, and providing technical expertise to the team
• Performing thorough code reviews to maintain quality standards and identify potential issues
• Assessing project scope, estimation and impact analysis

Do you have the right ingredients*? (Requirements)

• High proficiency  in Java or Kotlin (experience of 10-14 years in reputed product / relevant domain company)
• Experience  of API principals e.g REST
• Enjoys building well-engineered, usable and accessible systems
• Passionate about making users happy and seeing people use your product in the wild
• Ability to embrace an agile mindset focused on delivering usable software
• Adaptable to work in changing environments

Special Sauce* (Nice to Haves)

• Full Stack experience
• Experience with localisation and internationalization frameworks
• Experience in Hotel or Restaurant business domain
• Exposure to payments and integrations

What we use to make our dish (Our Tech Stack)

• A core of Java & Kotlin based backend services.
• React SPAs leveraging Tailwind, GraphQL and Storybook.
• Android app built in Java & Kotlin running in the restaurant.
• PostgreSQL and Dynamodb as core persistence.
• Pulsar, Camel and RabbitMQ for message-based integrations.
• And many more technologies that help us build a top class platform.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

Position Summary

This position is an exciting opportunity to join the Application Security division of Digital.ai, an industry leader specializing in client-side application protection. Our products embed security directly into applications, enabling them to defend themselves in untrusted environments. We are seeking a highly experienced Principal Software Engineer with expertise in modern web portal development, distributed event-processing systems, real-time analytics platforms, and AI/ML-driven data engineering workflows. The ideal candidate will help architect and optimize intelligent, data-intensive systems that support large-scale telemetry and security analytics. Experience with React, Node.js, Kafka, AWS Lambda, cloud-native engineering, and the use of AI/ML techniques to enhance data processing and insight generation is required.

What You Will Be Doing

You will join a team of cloud-native engineers building scalable, secure, and reliable cloud services powering our in-app protection products. Our services process billions of security events daily from more than 10 million devices worldwide.

As a full-stack Principal Engineer, you will:

• Drive architecture and implementation across the web stack, distributed systems, and AI-assisted analytics workflows.
• Leverage AI/ML techniques to strengthen event processing, anomaly detection, and data enrichment.
• Influence technical strategy across multiple teams, particularly around intelligent pipelines and analytics.
• Work in a fast-paced Agile/Scrum environment with frequent releases and high impact.

Primary Responsibilities

Web Application & Portal Engineering

• Lead the architectural design and development of scalable, secure web applications using React, Node.js, and TypeScript.
• Develop modular, maintainable UI components and back-end services aligned withengineering standards.
• Ensure adherence to performance, accessibility, and security best practices.Event Processing & Streaming Systems
• Architect and maintain distributed, event-driven systems using Apache Kafka, AWS Lambda, and related AWS services.
• Implement high-throughput pipelines for event ingestion, transformation, and enrichment.
• Apply AI-assisted techniques (e.g., automated anomaly scoring, content classification, behavioural clustering) to enhance streaming workflows.
• Ensure reliability, observability, and resilience across all streaming components.

Real-Time Analytics & Intelligent Data Engineering

• Design and support systems that deliver real-time analytics based on streaming and operational data.
• Collaborate with data engineering, analytics, and product teams to define schemas, telemetry models, KPIs, and AI-enriched data signals.
• Integrate lightweight ML models, heuristics, or AI-based scoring mechanisms intodashboards, alerts, and internal tools.
• Build data pipelines that support ML-assisted insights, including featurecomputation, data quality validation, and intelligent filtering.
• Work with ML frameworks or cloud AI services to operationalize models whereappropriate (e.g., anomaly detection, threat classification, event clustering).

Technical Leadership

• Drive architectural decisions involving high-scale distributed systems and AI/ML-enabled analytics components.
• Provide guidance on coding standards, intelligent pipeline patterns and data engineering best practices.
• Conduct design and code reviews, contributing to continuous process improvement.
• Mentor junior engineers and contribute to organization-wide technical initiatives.

Required Qualifications

• 8 to 12 years of professional software engineering experience.
• Advanced proficiency in React, Node.js, JavaScript/TypeScript, and modern front-end and back-end development practices.
• Hands-on experience with Apache Kafka, AWS Lambda, and event-driven serverless architectures.· Experience working with AWS API Gateways.
• Strong understanding of distributed systems, microservices, and REST/GraphQL API design.
• Experience with containerization (e.g., Docker), CI/CD pipelines, and AWS cloud-native environments.
• Experience on deploying and operating cloud-native applications on Kubernetes (EKS preferred).
• Experience with Postgres as a backend data store.
• Experience applying AI/ML techniques within data engineering or analytics workflows (e.g., anomaly detection, data classification, outlier scoring, clustering, or intelligent event enrichment).
• Proficiency using Python or cloud AI/ML services for productionizing lightweight models or heuristics.
• Strong background in unit, integration, and automated testing.
• Demonstrated ability to design scalable, highly available, and fault-tolerant systems.

Nice-to-Have Qualifications

• Domain knowledge of application security and security telemetry.
• Understanding the security threats and mitigation techniques.
• Experience with Apache Druid, ClickHouse, Snowflake for real-time analytics and OLAP workloads.
• Familiarity with MLOps concepts such as model monitoring, data drift detection, or automated retraining pipelines.
• Experience integrating LLMs or embedding-based techniques into data pipelines or developer tools
• Experience with DynamoDB, including NoSQL design patterns.
• Familiarity with AWS services such as ECS/EKS or Terraform.
• Understanding of event sourcing, CQRS, and advanced streaming patterns.
• Experience with observability tools (CloudWatch, Grafana, or Prometheus).

Digital.ai is firmly committed to merit-based hiring. We maintain compliance with US and International laws. We welcome everyone from all backgrounds, including age, race, color, gender, identity, gender expression, sex, pregnancy, national origin, ancestry, religion, physical or mental ability, medical condition, sexual orientation, marital status, citizenship status, protected military or veteran status, and believe that diversity is the foundation of innovation. 

For individuals with disabilities who would like to request an accommodation, please advise us within your job application or cover letter. 

FRAUD PREVENTION ALERT: Please note that Digital.ai does not use third party recruiters. In our efforts to protect you against possible impersonation please check the email address or are contacted by an unfamiliar/third party requesting please reach our directly to Digital.ai.  

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. 

Desired Skills & Experience 

• 4 - 5+ 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. 

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+ - 8+ 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. 

About the Role

We’re looking for a Staff Engineer – Core Platform to architect, scale, and evolve the distributed systems foundation that powers Interface.ai’s next-generation AI experiences.

This is a hands-on, high-impact engineering role — you will design and build core platform components that enable real-time AI interactions, secure orchestration, and low-latency execution across millions of concurrent user sessions.

The ideal candidate is a systems thinker who thrives on solving large-scale engineering challenges in distributed, event-driven environments — someone who obsesses over performance, reliability, and elegant architecture, and who elevates the technical bar for the entire organization.

What You’ll Own

As a Staff Engineer, you will be the technical backbone for the Core Platform team — defining architecture, mentoring teams, and ensuring engineering excellence across all systems.
You’ll focus on:

• Designing and scaling low-latency, fault-tolerant distributed systems serving real-time workloads.
  
  
• Architecting microservices and event-driven systems that are secure, composable, and resilient under scale.
  
  
• Integrating Vector Databases and Embedding Stores to support intelligent retrieval, RAG (Retrieval-Augmented Generation), and adaptive AI experiences.
  
  
• Partnering with AI and Product teams to embed LLMs and inference services into the Core Platform, ensuring performance and observability.
  
  
• Defining technical standards, best practices, and evolutionary architecture patterns across teams.
  
  
• Driving continuous improvement in code quality, observability, and deployment reliability.
  
  
• Acting as a technical mentor and multiplier — raising the bar for system design, code reviews, and debugging excellence.
  
  

What You’ll Do

• Architect and Build Distributed Systems: Design microservice-based architectures that enable scalability, low latency, and fault isolation for AI-driven features.
  
  
• Optimize System Performance: Own performance at the platform level — from network I/O and API design to database indexing and caching strategies.
  
  
• Enable AI Integrations: Work closely with LLM engineers to design APIs and data pipelines supporting RAG, embeddings, and model-inference use cases.
  
  
• Design Resilient Data Infrastructure: Implement streaming and async systems (Kafka, Pulsar, or similar) to handle high-volume event traffic.
  
  
• Drive Engineering Quality: Establish patterns for clean code, contracts, testing, and documentation. Lead architecture and code reviews across pods.
  
  
• Mentor and Coach: Elevate senior engineers through structured mentorship, design walkthroughs, and technical guidance.
  
  
• Champion Evolutionary Architecture: Build for change — advocate for modular, observable, and testable systems that can evolve with business needs.
  
  
• Improve Platform Resilience: Implement retry, backoff, rate-limiting, and circuit-breaker patterns to ensure uptime and reliability at scale.
  
  
• Collaborate Cross-Functionally: Work with AI, data, DevOps, and product teams to define shared contracts, SLAs, and infrastructure standards.
  
  

What We’re Looking For

Required Qualifications

• Experience: 8+ years of experience in backend or platform engineering, including 2+ years in high-scale B2C or distributed systems environments.
  
  
• Distributed Systems Mastery: Deep understanding of scalability, consistency, concurrency control, and fault tolerance.
  
  
• Low-Latency Systems Expertise: Proven track record designing systems with strict SLA and sub-second response times.
  
  
• Microservices Architecture: Strong experience building, deploying, and maintaining service-oriented architectures with APIs, event streams, and async messaging.
  
  
• Vector DBs & Embeddings: Hands-on experience with Weaviate, Pinecone, Qdrant, FAISS, or similar; strong grasp of RAG patterns and semantic retrieval.
  
  
• Programming Proficiency: Expertise in Go, Rust, Java, or Python, and familiarity with modern frameworks (gRPC, GraphQL, REST).
  
  
• Data Layer Knowledge: Solid understanding of SQL/NoSQL databases (PostgreSQL, Cassandra, DynamoDB) and caching systems (Redis, Memcached).
  
  
• Resilience & Observability: Experience designing with telemetry, distributed tracing, chaos testing, and monitoring (Prometheus, OpenTelemetry).
  
  
• Engineering Quality Mindset: Passion for clean code, automated testing, CI/CD, and maintainability.
  
  
• Bar-Raising Leadership: Experience mentoring teams, enforcing code quality standards, and elevating design practices.
  
  

Preferred Qualifications

• Experience building or scaling real-time personalization or recommendation systems.
  
  
• Prior exposure to LLM serving, RAG pipelines, and LLMOps frameworks.
  
  
• Familiarity with Kafka, Flink, or Beam for data streaming.
  
  
• Contributions to open-source projects in distributed systems or AI tooling.
  
  
• Deep understanding of cloud-native architectures (Kubernetes, Istio, Terraform).
  
  

What Makes This Role Special

• You’ll define and scale the core technical foundation for AI systems serving millions of users.
  
  
• You’ll collaborate with world-class engineers across AI, platform, and product to deliver real-time, intelligent experiences.
  
  
• You’ll raise the engineering bar — shaping how code is written, reviewed, and deployed across teams.
  
  
• You’ll lead by example: mentoring senior engineers while remaining hands-on in architecture, design, and implementation.
  
  
• You’ll be part of an organization where AI-first thinking, evolutionary architecture, and engineering craftsmanship are core values.
  
  
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