Job summary: 

• We are looking for a talented Enterprise Account Executive / Business Development Manager to join our fast-growing Brandwatch Sales organisation. You will be responsible for driving new enterprise revenue in India with a strong focus on Trajaan, while also growing strategic accounts across the broader Brandwatch portfolio.
• This is a hybrid AE/AM role suited to a highly commercial, enterprise seller who can both self-generate pipeline and expand existing customer relationships. The ideal candidate will have a strong track record in enterprise SaaS sales with a skill-set including, but not limited to, prospecting, pipeline generation, complex deal management, executive stakeholder engagement, renewal negotiation, upselling and especially cross-selling. A key part of this role will be leading with Trajaan as a strategic growth priority, while identifying opportunities to expand into other Brandwatch solutions where relevant.
• You will drive growth by engaging some of India’s largest organisations, challenging the way customers think about search intelligence, consumer intelligence and digital strategy, and positioning how Trajaan and Brandwatch can support those evolving priorities. You would be a great fit if you are comfortable building from the ground up, owning the full commercial cycle, and balancing a hunter mindset with strong account growth instincts.

What you will do:

• Drive new enterprise business growth in India, with a primary focus on Trajaan and a secondary focus on the wider Brandwatch portfolio;
• Build and manage a robust pipeline through proactive outbound prospecting, self-generated opportunities, partner collaboration and internal support functions;
• Own the full sales cycle from initial outreach and discovery through solutioning, commercial negotiation and contract execution;
• Lead land-and-expand motions across strategic accounts, identifying upsell and cross-sell opportunities;
• Build long-term relationships with senior stakeholders across Marketing, Insights, Digital, Strategy, Communications and related enterprise functions;
• Act as a trusted advisor to customers by challenging the status quo and promoting how Trajaan and Brandwatch can support growth, visibility and competitive advantage;
• Maintain constant engagement with accounts post-sale, partnering with Customer Success and internal stakeholders to drive adoption, value realisation, retention and expansion;
• Identify commercial risk and collaborate with internal teams to clear blockers, protect revenue and support successful renewals where relevant;
• Be the primary point of contact for the customer on all commercial and contractual matters within your portfolio;
• Partner with internal Brandwatch and Cision stakeholders to align account plans with the customer’s business priorities and strategic goals;
• Develop strong market knowledge across enterprise sectors in India and stay informed on trends across search, LLM visibility, digital intelligence, consumer behaviour and competitive landscape;
• Possess excellent product knowledge across Trajaan and Brandwatch solutions and lead tailored product demonstrations aligned to customer needs.
• Maintain accurate forecasting, pipeline hygiene and account activity within CRM and reporting systems.

What you will have:

• A strong background in enterprise sales and business development, with SaaS experience strongly preferred;
• 6+ years of experience in a quota-carrying sales role, ideally across a mix of new business acquisition and account growth;
• Proven ability to self-generate pipeline and win new enterprise logos in a competitive market;
• Drive and ambition to achieve and exceed sales quotas;
• Commercial acumen and comfort working towards ambitious growth targets in a highly accountable environment;
• Experience managing complex, multi-stakeholder sales cycles and negotiating commercial agreements with enterprise customers;
• Experience in growing existing client relationships through upsell, cross-sell and renewal ownership where required;
• A results-oriented, highly motivated and enthusiastic attitude, with the ability to work independently in a fast-paced environment;
• Familiarity operating in a high-growth, high-velocity sales environment;
• Outstanding consultative selling skills, including objection handling, negotiation, influencing and value-based solution selling;
• Ability to build strong relationships with internal and external stakeholders;
• Excellent English communication skills; additional Indian regional language capability would be an advantage;
• Deep interest in or knowledge of search intelligence, digital intelligence, consumer insights, social media, marketing technology or customer experience.

Soft skills:

• Top-class presentation and communication skills.
• Excellent analytical, problem-solving and decision-making skills.
• Detail-oriented and persuasive.
• Strong sense of ownership;
• Strong commercial curiosity and a proactive mindset;
• Proficiency with tools such as Salesforce, Salesloft, 6Sense or similar;
• Use of, implementation and understanding of sales processes and methodologies.

Nice to have:

• Experience selling search intelligence, consumer intelligence, marcom or insights-focused solutions;
• Experience selling into enterprise accounts in India;
• Familiarity with Sandler, BANT, MEDDPICC or other similar sales methodologies.
• Experience working with partner or reseller ecosystems.

Role Overview
We are seeking a Staff Frontend Engineer to be the technical anchor for our frontend capability. This role goes beyond feature delivery — you will define the frontend architecture, establish the component design system, own the Next.js application structure, drive performance standards, and mentor Senior and mid-level frontend engineers. You will build the most complex, data-intensive UI surfaces: real-time attribution dashboards, AI powered campaign builders, and platform-embedded intelligence widgets — all in React + Next.js stack integrated with Elasticsearch-powered search and streaming AI responses.  

Key Responsibilities
• Own and evolve the frontend architecture: Next.js App Router structure, component boundaries, state management strategy (Redux), and data-fetching patterns — applying hexagonal UI principles where the component layer is decoupled from specific backend service contracts.

• Design and build the most technically complex UI surfaces: real-time attribution dashboards (streaming data), AI-powered campaign builder (LLM response streaming), Elasticsearch-backed customer search with faceted filtering, and platform-embedded opportunity cards.

• Define the component design system: atomic component library, theming contracts, accessibility standards (WCAG 2.1), and Storybook-based documentation.

• Establish frontend performance standards: Core Web Vitals targets, bundle size budgets, SSR/SSG strategy with Next.js, lazy loading, and virtualization for large data tables.

• Lead Next.js architecture decisions: App Router vs. Pages Router tradeoffs, RSC (React Server Components) applicability, streaming SSR for AI-generated content, and API route design.

• Integrate AI-native frontend patterns: streaming LLM responses into UI components, real-time score updates from Redis/Aerospike via SSE, and Elasticsearch typeahead search. 

• Drive code quality through design reviews, code reviews, pair programming, and frontend-specific engineering standards.

• Mentor Senior and mid-level frontend engineers — setting the bar for component design, test coverage, and performance discipline.

• Collaborate closely with backend Staff Engineers to define API contracts and with designers to implement pixel-perfect, accessible UIs

Skills & Qualifications

• 8+ years of frontend engineering experience with deep React and Next.js expertise in production systems.

• Mastery of Next.js 14+ App Router, React Server Components, streaming SSR, and static generation — knowing when to apply each pattern.

• Strong TypeScript expertise: type safety across component props, API contracts, Redux store shape, and server/client boundaries.

• Deep Redux expertise: slice design, selector optimization, middleware patterns, and RTK Query for data fetching.

• Proven experience building data-intensive dashboards with real-time data (WebSocket, SSE, or polling) and chart libraries (Recharts, D3.js).

• Experience integrating Elasticsearch-powered search UIs: typeahead, faceted search, and result ranking display.

• Strong frontend performance engineering: bundle analysis, code splitting, memoization, virtualization, and Core Web Vitals optimization.

• Experience establishing and maintaining component design systems with accessibility standards.

• Experience mentoring engineers and raising the technical bar across a frontend team. 

Good to Have

• Experience streaming LLM/AI-generated content into React UI components (token streaming, partial rendering patterns).

• Familiarity with platform-embedded micro-frontend patterns (module federation or iframe-based embedding).

• Background in automotive retail, eCommerce analytics, or SaaS BI/reporting platforms.

• Experience with Storybook for component documentation and visual regression testing. 

Role: GenAI Lead Engineer

Experience: 8+ years total (with significant hands-on GenAI / LLM work)

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
• Lead the end-to-end design and implementation of Generative AI solutions.
• Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
• Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
• Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
• Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
• Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
• Ensure scalability, performance, and security of AI solutions deployed in production.
• Integration and Deployment:
• API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
• Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
• Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
• Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
• Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
• Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
• Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
• Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
• Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
• Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Technical Skills:
• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
• Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
• Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
• Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
• Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
• Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
• Proven track record of leading AI projects from inception to production.
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
• Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).

Role Overview
We are seeking a senior, technically strong Product Manager to own platform capabilities across one of our engineering Scrum teams while driving customer-facing outcomes and continuous improvement. This role requires close collaboration with Engineering, AI, and platform teams, along with hands-on understanding of event-driven systems, agentic AI integration, scalable service design, and data-driven product development.

Key Responsibilities
• Own the product backlog for a Scrum team — writing clear, actionable user stories, acceptance criteria, and feature specifications aligned with business goals.
• Partner closely with Engineering and AI teams to deliver high-quality solutions across Java microservices, Kafka event pipelines, and agentic platform integrations.
• Collaborate with platform and infrastructure teams to ensure seamless integrations, well-defined data contracts, and API alignment.
• Track success metrics, adoption, and outcomes — iterating rapidly based on data and field feedback.
• Author Intent definitions, Skill specifications, and Policy configurations for the agentic platform layer (PRDas-Code approach).
• Design and maintain golden dataset scenarios used to validate intelligent capabilities before release.
• Drive change management and adoption of new features, tools, and platform capabilities.
• Build and maintain automations using workflow tools (Zapier or equivalent) to streamline internal processes.
• Demonstrate strong understanding of RESTful APIs, webhooks, and authentication mechanisms; troubleshoot integration issues hands-on.
• Work with data teams to define schemas, reporting views, and analytics instrumentation.
• Facilitate prioritization discussions, manage stakeholder expectations, and communicate trade-offs clearly across Engineering, Design, and Leadership.

Skills & Qualifications
• 6+ years of Product Management experience, preferably in platform, data-driven, or AI-enabled products.
• Strong experience collaborating with engineering teams on technical products — comfortable reading system designs, API specs, and data models.
• Proven analytical and problem-solving skills with a data-driven mindset; experience defining and tracking product KPIs.
• Hands-on experience with RESTful APIs, webhooks, and system integrations (ERP, CRM, data platforms, or cloud services).
• Familiarity with AI systems, LLM-based tools, and agentic AI patterns (intent routing, skill/policy design, MCP tools).
• Experience designing scalable, maintainable solution architectures in collaboration with engineering.
• Excellent verbal and written communication skills; strong stakeholder management across technical and non-technical audiences.
• Structured problem-solving and critical thinking; ability to navigate complex system trade-offs.
• Bachelor's or Master's degree in IT, Computer Science, Business Administration, or a related field.

Good to Have
• Experience authoring PRD-as-Code artifacts: Intent definitions, Skill specs, Policy configurations.
• Background in marketing technology, CDP, or customer data platforms.
• Experience with LMS platforms and user enablement programs.
• Prior experience in automotive retail or dealer technology.

Perks & Benefits
• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies

Job Description

You will develop enterprise-grade frontend experiences embedded within our core platform and collaborate closely with designers, backend engineers, and product managers to deliver a world-class, AI-native user experience. You will build scalable, performant React + Next.js applications that surface real-time intelligence, campaign management interfaces, and data-rich dashboards — deeply integrated with our backend services and platform component framework.

Key Responsibilities
• Design and build responsive, reusable UI components using ReactJS and Next.js — including data visualization dashboards, campaign management interfaces, and customer intelligence widgets.
• Develop large-scale, cloud-ready frontend applications integrated with backend REST APIs, real-time data streams, and Elasticsearch-powered search experiences.
• Manage application state using Redux, ensuring seamless synchronization with backend microservices.
• Build platform-embedded frontend components following the hexagonal UI principle — components are independent, composable, and decoupled from specific data sources via port interfaces.
• Leverage Next.js SSR and SSG capabilities where appropriate for performance-critical views and SEO relevant surfaces.
• Collaborate with product, design, and backend teams to rapidly prototype and deliver high-quality, data-rich features.
• Ensure usability, performance, security, and visual consistency across environments and devices.
• Diagnose and fix UI bugs, rendering performance issues, and frontend bottlenecks.
• Write high-quality, maintainable code with thorough unit and integration tests.
• Follow Tekion UI, design, and engineering best practices.

Skills & Experience
• 3-5 years of experience in frontend engineering; Bachelor's degree in Computer Science or a related field.
• Strong hands-on expertise with React, Next.js, JavaScript/TypeScript, and Redux.
• Solid knowledge of HTML, CSS, and web standards (REST, HTTP, JSON, DOM, W3C).
• Experience building enterprise-grade SaaS applications with real-time data and complex state management requirements.
• Familiarity with Next.js App Router, SSR, SSG, and API routes.
• Excellent understanding of frontend performance: code splitting, lazy loading, memoization, virtualization.
• Experience with Git and project management tools (e.g., JIRA).
• Proven experience delivering scalable, high-performance frontend systems with thorough test coverage.
• Strong sense of ownership and bias for action in a fast-paced startup environment.

Preferred Skills
• Experience integrating AI-generated content and LLM-streamed responses into frontend components.
• Familiarity with data visualization libraries (Recharts, D3.js) for analytics and reporting dashboards.
• Experience building embedded micro-frontend components within larger platform shells.
• Exposure to Elasticsearch-powered search UI patterns (faceted search, typeahead, result ranking).

Perks & Benefits
• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

Role Overview:

We are looking for a hands-on Product Architect / Engineer to design and build an AI-driven operations platform focused on intelligent automation, insights, and optimization across cloud, network, and application operations.This role blends product thinking, architecture, and deep engineering across AI/ML and Agentic AI systems.

Key Responsibilities:

• Architect and build the agentic AI platform leveraging AI, ML, and Agentic AI frameworks
• Design multi-agent systems for use cases for operations domains like Cloud Ops, NetworkOps, ServiceDesk, root cause analysis, anomaly detection, and predictive insights
• Develop data pipelines and telemetry fabric for ingesting and processing large-scale operational data (logs, metrics, traces, topology)
• Build and integrate LLM-powered copilots and autonomous agents for operations 
• Define product architecture, including microservices, APIs, event-driven systems, and scalable cloud-native patterns
• Translate business needs into AI-driven product features and accelerators
• Collaborate with product, operations, and engineering teams to deliver end-to-end capabilities

Key Skills:

• Strong experience in product architecture and full-stack engineering
• Hands-on expertise in:
• AI/ML (model development, inference, MLOps)
• LLMs and Agentic AI frameworks (multi-agent orchestration, reasoning systems)
• Data engineering (streaming, batch, real-time analytics)
• Proficiency in Python and modern frameworks
• Experience with cloud platforms (AWS, Azure) and cloud-native architecture
• Agent framework experience – Microsoft agent framework, langgraph and langchain.
• Strong understanding of:
• Observability systems (logs, metrics, traces)
• AIOps / IT operations platforms
• API design and microservices architecture
• Familiarity with vector databases, embeddings, RAG architectures, and knowledge graphs

Good to Have:

• Experience building autonomous AI agents for IT/network/application operations
• Exposure to FinOps, Cloud Cost Optimization,
• Knowledge of network topology, infrastructure ops, or ITSM tools
• Experience with real-time decisioning systems and event correlation engines

Job Description
You will develop enterprise-grade frontend experiences embedded within our core platform and collaborate closely with designers, backend engineers, and product managers to deliver a world-class, AI-native user experience. You will build scalable, performant React + Next.js applications that surface real-time intelligence, campaign management interfaces, and data-rich dashboards — deeply integrated with our backend services and platform component framework.

Key Responsibilities
• Design and build responsive, reusable UI components using ReactJS and Next.js — including data visualization dashboards, campaign management interfaces, and customer intelligence widgets.
• Develop large-scale, cloud-ready frontend applications integrated with backend REST APIs, real-time data streams, and Elasticsearch-powered search experiences.
• Manage application state using Redux, ensuring seamless synchronization with backend microservices.
• Build platform-embedded frontend components following the hexagonal UI principle — components are independent, composable, and decoupled from specific data sources via port interfaces.
• Leverage Next.js SSR and SSG capabilities where appropriate for performance-critical views and SEO relevant surfaces.
• Collaborate with product, design, and backend teams to rapidly prototype and deliver high-quality, data-rich features.
• Ensure usability, performance, security, and visual consistency across environments and devices.
• Diagnose and fix UI bugs, rendering performance issues, and frontend bottlenecks.
• Write high-quality, maintainable code with thorough unit and integration tests.
• Follow Tekion UI, design, and engineering best practices.

Skills & Experience
• 5+ years of experience in frontend engineering; Bachelor's degree in Computer Science or a related field.
• Strong hands-on expertise with React, Next.js, JavaScript/TypeScript, and Redux.
• Solid knowledge of HTML, CSS, and web standards (REST, HTTP, JSON, DOM, W3C).
• Experience building enterprise-grade SaaS applications with real-time data and complex state management requirements.
• Familiarity with Next.js App Router, SSR, SSG, and API routes.
• Excellent understanding of frontend performance: code splitting, lazy loading, memoization, virtualization.
• Experience with Git and project management tools (e.g., JIRA).
• Proven experience delivering scalable, high-performance frontend systems with thorough test coverage.
• Strong sense of ownership and bias for action in a fast-paced startup environment.

Preferred Skills
• Experience integrating AI-generated content and LLM-streamed responses into frontend components.
• Familiarity with data visualization libraries (Recharts, D3.js) for analytics and reporting dashboards.
• Experience building embedded micro-frontend components within larger platform shells.
• Exposure to Elasticsearch-powered search UI patterns (faceted search, typeahead, result ranking).

Perks & Benefits
• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

The Role

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

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

What You Will Do

• Build & Deploy (60%):

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

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

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

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

• Customer Engineering (40%):

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

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

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

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

The "Must-Haves"

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

The "Why You" (Soft Skills)

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

What will set you apart

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

Tech Stack

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

Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

What we’re looking for  

We’re looking for a Software Engineer III who is passionate about building reliable, scalable backend systems and enjoys working across the stack when needed. You are a hands‑on engineer who thrives on solving real‑world problems, writing clean and maintainable code, and collaborating closely with teammates to deliver high‑quality features end‑to‑end. 

You bring strong engineering fundamentals, a growth mindset, and the ability to work independently on well‑scoped projects — owning medium‑sized features from design through deployment in alignment with our engineering best practices. You’re comfortable contributing to technical discussions, making thoughtful trade‑offs, and following established architectural patterns as you deepen your understanding of our systems. 

This role is fully remote, based in India and offers the opportunity to meaningfully influence backend architecture, shape engineering best practices, and work with a mission-driven, high-performing team.  

What you’ll own  

As a Software Engineer III, you will have clear ownership over features, with opportunities to contribute across the stack:  

• Own and deliver small to medium-sized backend features end-to-end: From technical discovery and design through implementation, testing, deployment and iteration 

• Take technical ownership of one or more non‑critical backend services or components: Ensuring they remain reliable, maintainable, well‑documented, and easy to extend. 

• Write clean, modular, testable code: Primarily in Ruby, Ruby on Rails, and Python, while contributing to frontend code when needed to support full‑stack feature delivery. 

• Contribute to the design and evolution of our APIs: Including GraphQL and REST endpoints that power frontend and partner‑facing applications, following established architectural patterns and best practices. 

• Ensure strong observability and operational health of owned services: Through logging, monitoring, alerting, and contributing to root‑cause analysis and follow‑through improvements. 

• Actively participate in technical discussions: Bringing thoughtful perspectives that balance simplicity, long‑term maintainability, and performance as you deepen your understanding of Perch’s systems. 

• Support team productivity through high‑quality code reviews and collaboration: Sharing context, helping unblock others, and contributing to a strong engineering culture. 

What you’ll do  

• Design and build scalable, resilient backend systems using Ruby on Rails, Python and PostgreSQL  

• Contribute to implementation of complex features and integrations, including external systems such as Salesforce  

• Take technical design decisions independently for your features 

• Own and evolve GraphQL services that power frontend and partner-facing applications  

• Improve system reliability through testing, monitoring, alerting, and operational best practices  

• Ship production-ready code frequently using a modern CI/CD pipeline  

• Review code and designs with a strong focus on maintainability, performance, and long-term impact  

What will help you succeed  

Experience & leadership  

• 4+ years of experience building and operating high-availability backend systems  

• Demonstrated experience delivering backend features and owning systems 

• Strong fundamentals in system design, API design, and data modelling  

• Ability to clearly communicate technical decisions and trade-offs to both technical and non-technical stakeholders 

• Actively represent engineering team in key discussions with US stakeholders 

• Proven experience mentoring junior engineers and raising the technical bar of a team  

• Comfortable working in ambiguous problem spaces and iterating toward robust solutions  

Backend & infrastructure  

• Strong experience with Python or Ruby, including proficiency in at least one web framework: 

• Ruby on Rails 

• FastAPI, Django or Flask 

• Working knowledge of ReactJS, with the ability to contribute to frontend components to support full‑stack delivery 

• Advanced SQL skills and experience with PostgreSQL or similar relational databases  

• Hands-on experience with AWS services such as S3, SQS, SES, EventBridge, or similar cloud-native services.  

• Containerization using Docker  

• Exposure to distributed systems or platform engineering  

• Familiarity with background jobs, async processing, and event-driven workflows  

Bonus points for  

• Experience integrating with Salesforce or other enterprise platforms  

• Experience designing and owning  GraphQL APIs (Apollo or similar)  

• Strong opinions (loosely held) on backend architecture, scalability, and system design  

• Exposure to AI-assisted engineering—such as using modern AI tools for coding, debugging, testing, documentation, or exploring LLM-based workflows in backend systems  

• Familiarity with observability and distributed tracing tools such as OpenTelemetry, Jaeger, Prometheus, or similar  

• Experience with container orchestration and deployment using Kubernetes and Helm charts  

• Passion for sustainability, clean energy, and building mission-driven products  

What success looks like in this role  

• Backend systems scale reliably as usage, data volume, and complexity grow  

• Engineers move faster due to clear APIs, architecture, and standards  

• Production issues are identified early and resolved with lasting fixes  

• Technical debt is addressed proactively rather than reactively  

• The backend platform enables product teams instead of limiting them  

Benefits:  Apart from Fixed Base Salary potential candidates are eligible for following benefits  

• Competitive compensation based on market standards.  
• Flexible Leave Policy  

• Office is in the heart of the city in case you need to step in for any purpose.  

• Medical Insurance (1+5 Family Members)  

• We provide comprehensive coverage including accident policy and life Insurance.   

• Annual performance cycle  

• Quarterly team engagement activities and rewards & recognitions  

• L&D programs to foster professional growth  

• A supportive engineering culture that values diversity, empathy, teamwork, trust, and efficiency   

Eliminating carbon footprints, eliminating carbon copies. Here at Perch, we cultivate diversity, celebrate individuality, and believe unique perspectives are key to our collective success in creating a clean energy future. Perch is committed to equal employment opportunities regardless of race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, protected veteran status, or any status protected by applicable federal, state, or local law. While we are currently unable to consider candidates who will require visa sponsorship, we welcome applications from all qualified candidates eligible to work in India.  
  
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request

Software Engineer III 
  
  

Who we are  

Perch Energy is a mission-driven company that focuses on expanding access to clean and affordable energy through community solar. Community solar breaks down the traditional barriers preventing most people from participating in the renewable energy economy by making it accessible, affordable, and more equitable for all. We work in several states across the US to bring community solar to communities and individuals who can most benefit from a more inclusive energy system. By managing the customer experience for solar farm owners, Perch is able to bring electricity bill savings to the masses, from renters and homeowners to businesses, institutions, municipalities and more by connecting them to community solar projects in their area. Perch isn't just a for-profit company, we're a for-purpose company—accelerating the shift to renewables nationwide. Everyone deserves to benefit from clean energy. Everyone has a place on this Perch!  

What we’re looking for  

We’re looking for a Software Engineer III who is passionate about building reliable, scalable backend systems and enjoys working across the stack when needed. You are a hands‑on engineer who thrives on solving real‑world problems, writing clean and maintainable code, and collaborating closely with teammates to deliver high‑quality features end‑to‑end. 

You bring strong engineering fundamentals, a growth mindset, and the ability to work independently on well‑scoped projects — owning medium‑sized features from design through deployment in alignment with our engineering best practices. You’re comfortable contributing to technical discussions, making thoughtful trade‑offs, and following established architectural patterns as you deepen your understanding of our systems. 

This role is fully remote, based in India and offers the opportunity to meaningfully influence backend architecture, shape engineering best practices, and work with a mission-driven, high-performing team.  

What you’ll own  

As a Software Engineer III, you will have clear ownership over features, with opportunities to contribute across the stack:  

• Own and deliver small to medium-sized backend features end-to-end: From technical discovery and design through implementation, testing, deployment and iteration 

• Take technical ownership of one or more non‑critical backend services or components: Ensuring they remain reliable, maintainable, well‑documented, and easy to extend. 

• Write clean, modular, testable code: Primarily in Ruby, Ruby on Rails, and Python, while contributing to frontend code when needed to support full‑stack feature delivery. 

• Contribute to the design and evolution of our APIs: Including GraphQL and REST endpoints that power frontend and partner‑facing applications, following established architectural patterns and best practices. 

• Ensure strong observability and operational health of owned services: Through logging, monitoring, alerting, and contributing to root‑cause analysis and follow‑through improvements. 

• Actively participate in technical discussions: Bringing thoughtful perspectives that balance simplicity, long‑term maintainability, and performance as you deepen your understanding of Perch’s systems. 

• Support team productivity through high‑quality code reviews and collaboration: Sharing context, helping unblock others, and contributing to a strong engineering culture. 

What you’ll do  

• Design and build scalable, resilient backend systems using Ruby on Rails, Python and PostgreSQL  

• Contribute to implementation of complex features and integrations, including external systems such as Salesforce  

• Take technical design decisions independently for your features 

• Own and evolve GraphQL services that power frontend and partner-facing applications  

• Improve system reliability through testing, monitoring, alerting, and operational best practices  

• Ship production-ready code frequently using a modern CI/CD pipeline  

• Review code and designs with a strong focus on maintainability, performance, and long-term impact  

What will help you succeed  

Experience & leadership  

• 4+ years of experience building and operating high-availability backend systems  

• Demonstrated experience delivering backend features and owning systems 

• Strong fundamentals in system design, API design, and data modelling  

• Ability to clearly communicate technical decisions and trade-offs to both technical and non-technical stakeholders 

• Actively represent engineering team in key discussions with US stakeholders 

• Proven experience mentoring junior engineers and raising the technical bar of a team  

• Comfortable working in ambiguous problem spaces and iterating toward robust solutions  

Backend & infrastructure  

• Strong experience with Python or Ruby, including proficiency in at least one web framework: 

• Ruby on Rails 

• FastAPI, Django or Flask 

• Working knowledge of ReactJS, with the ability to contribute to frontend components to support full‑stack delivery 

• Advanced SQL skills and experience with PostgreSQL or similar relational databases  

• Hands-on experience with AWS services such as S3, SQS, SES, EventBridge, or similar cloud-native services.  

• Containerization using Docker  

• Exposure to distributed systems or platform engineering  

• Familiarity with background jobs, async processing, and event-driven workflows  

Bonus points for  

• Experience integrating with Salesforce or other enterprise platforms  

• Experience designing and owning  GraphQL APIs (Apollo or similar)  

• Strong opinions (loosely held) on backend architecture, scalability, and system design  

• Exposure to AI-assisted engineering—such as using modern AI tools for coding, debugging, testing, documentation, or exploring LLM-based workflows in backend systems  

• Familiarity with observability and distributed tracing tools such as OpenTelemetry, Jaeger, Prometheus, or similar  

• Experience with container orchestration and deployment using Kubernetes and Helm charts  

• Passion for sustainability, clean energy, and building mission-driven products  

What success looks like in this role  

• Backend systems scale reliably as usage, data volume, and complexity grow  

• Engineers move faster due to clear APIs, architecture, and standards  

• Production issues are identified early and resolved with lasting fixes  

• Technical debt is addressed proactively rather than reactively  

• The backend platform enables product teams instead of limiting them  

Benefits:   

• Competitive compensation based on market standards.  

Apart from Fixed Base Salary potential candidates are eligible for following benefits  

• Flexible Leave Policy  

• Office is in the heart of the city in case you need to step in for any purpose.  

• Medical Insurance (1+5 Family Members)  

• We provide comprehensive coverage including accident policy and life Insurance.   

• Annual performance cycle  

• Quarterly team engagement activities and rewards & recognitions  

• L&D programs to foster professional growth  

• A supportive engineering culture that values diversity, empathy, teamwork, trust, and efficiency   

Eliminating carbon footprints, eliminating carbon copies. Here at Perch, we cultivate diversity, celebrate individuality, and believe unique perspectives are key to our collective success in creating a clean energy future. Perch is committed to equal employment opportunities regardless of race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, protected veteran status, or any status protected by applicable federal, state, or local law. While we are currently unable to consider candidates who will require visa sponsorship, we welcome applications from all qualified candidates eligible to work in India.  
  
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request 

About the Team At Business Technology, we use Appian to run Appian. We are launching our first internal AI team to build the foundation for how our global company works. This team won't just use AI, they will build the brain of the enterprise, spanning everything from predictive intelligence in our data warehouse to the GenAI infrastructure that powers our internal autonomous agents.

We are hiring a founding group of engineers to kickstart this mission. As an AI Engineer on this team, you won’t be maintaining legacy systems; you’ll be building from the ground up. You will own the full spectrum of AI: crafting predictive ML models to find insights in our data warehouse and architecting GenAI systems that allow any employee to interact with enterprise knowledge through intelligent agents.

If you want to be part of the original team that defines internal AI for a leading automation company, this is your moment.

PLEASE NOTE: This is a midlevel role and is aimed at people with 3+ years experience

What you’ll do:

• Build the AI Platform: Design, deploy, and scale GenAI infrastructure on GCP Vertex AI (preferred) or AWS Bedrock.
• Build & Operate MCP Servers: Develop and maintain Model Context Protocol (MCP) servers that expose enterprise systems (databases, APIs, internal tools) as structured, AI-consumable capabilities.
• Design the Tool Layer: Build the tool registry and invocation framework that allows agents to interact with internal systems safely and reliably including schema design, access controls, and error handling.
• Engineer Agent-to-Agent Infrastructure: Architect the communication and coordination layer that allows specialized agents to delegate tasks, share context, and compose into larger autonomous workflows.
• Own the Retrieval Layer: Architect and operate RAG systems, including vector stores, embedding pipelines, chunking strategies, and retrieval evaluation frameworks.
• Establish AI Reliability: Instrument AI systems with logging, tracing, latency monitoring, and evaluation hooks so agents can be trusted, debugged, and improved in production.

Required Qualifications:

• AI Infrastructure Experience: Professional experience building and deploying production-grade GenAI systems on GCP Vertex AI or AWS Bedrock including LLM APIs, agent frameworks, and RAG pipelines.
• Python Mastery: Deep proficiency in Python and common AI/ML libraries (e.g., LangChain, LlamaIndex, OpenAI SDK, Google Cloud AI SDK).
• Agentic Systems: Hands-on experience building multi-step, tool-calling AI agents that operate reliably in production including tool schema design, structured outputs, and failure handling.
• MCP or Tool Protocol Experience: Familiarity with Model Context Protocol (MCP) or equivalent patterns for exposing enterprise resources to AI systems as callable, permissioned tools.
• Vector & Retrieval Systems: Experience with vector databases (Pinecone, pgvector, or similar) and embedding-based retrieval at scale.
• Technical Foundation: B.S. in Computer Science, Engineering, or a related technical field.
• The Pioneer Mindset: A self-starter who is excited to be part of a "first-of-its-kind" team and thrives in environments where you are building the playbook.

Preferred Qualifications:

• Multi-Agent Architectures: Experience designing orchestrator/subagent patterns, agent handoff protocols, or systems where multiple AI models coordinate to complete complex tasks (e.g., using frameworks like LangGraph, CrewAI, or AutoGen).
• AI Observability: Experience with LLM evaluation frameworks, prompt regression testing, or agent trace monitoring (e.g. custom eval pipelines).
• Data Warehouse Integration: Familiarity with SQL and pulling data from Snowflake or BigQuery to ground AI agents in live business context.
• Appian Exposure: Experience with the Appian platform or interest in integrating AI agents into low-code automation workflows.
• Predictive ML (Nice to Have): Some familiarity with ML fundamentals is a plus, but not a focus of this role.

This role is based at our Chennai office in Brigade World Trade Center Chennai. Appian was built on a culture of in-person collaboration, which we believe is a key driver of our mission to be the best. Employees hired for this position are expected to be in the office 5 days a week to foster that culture and ensure we continue to thrive through shared ideas and teamwork. We believe being in the office provides more opportunities to come together and celebrate working with the exceptional people across Appian.  

Role Overview

We are looking for a Senior Backend Engineer to design, build, and scale robust backend services that power complex business workflows. This role requires strong ownership, deep Java expertise, a solid grounding in hexagonal architecture, and the ability to collaborate effectively across product, QA, AI/ML, and engineering teams in a fast-moving, AI-native environment.

Key Responsibilities

• Design and build Java (Spring Boot 3.x) microservices following hexagonal architecture — clean domain logic isolated from MongoDB, PostgreSQL, Cosmos DB, and Kafka adapter implementations.

• Develop and maintain REST APIs, Kafka event consumers/producers, and domain service logic for campaign, scoring, attribution, and customer profile workflows.

• Build and manage MongoDB document schemas and PostgreSQL relational schemas for high-throughput, multi-tenant use cases. 

• Implement Cosmos DB data models for event and state storage with appropriate partition key and consistency strategies.

• Take end-to-end ownership of components — from domain design and hexagonal adapter implementation through deployment and ongoing optimization.

• Integrate with Elasticsearch for campaign search, customer lookup, and full-text query workloads.

• Configure and tune Redis or Aerospike for frequency cap enforcement, scoring cache, and session state management.

• Identify and resolve performance bottlenecks across services, event pipelines, and data layers.

• Participate actively in design discussions, architecture decisions, and code reviews.

• Mentor Junior engineers and act as a role model for code quality, hexagonal design, and AI-native engineering best practices.

Skills & Qualifications

• 5+ years of backend engineering experience; Bachelor's or Master's degree in Computer Science or a related field.

• Strong Java 21 and Spring Boot 3.x expertise; solid grasp of hexagonal architecture and clean domain modeling.

• Experience with Kafka: consumer/producer patterns, at-least-once delivery, idempotent processing, and event-driven service design.

• Hands-on MongoDB experience: document schema design, indexing, aggregation pipelines, multi-tenant isolation.

• PostgreSQL experience: schema design, query optimization, migration management.

• Familiarity with Cosmos DB or equivalent distributed key-value / document stores.

• Experience with Elasticsearch for search and analytics workloads.

• Experience with Redis or Aerospike for high-throughput caching patterns.

• Familiarity with cloud-based systems on AWS (EKS, MSK, S3).

• Strong debugging, performance tuning, and system optimization skills.

• Familiarity with Agile/Scrum development practices and CI/CD pipelines.

Good to Have

• Experience with Temporal for workflow orchestration.

• Familiarity with AI-native integration patterns: MCP tool registration, scoring API contracts, LLM gateway usage.

• Working knowledge of Python for understanding AI/ML service outputs and integrating scoring results.

• Background in enterprise-scale SaaS platforms: eCommerce, supply chain, or similar. 

Job Description

We are seeking a Staff Backend Engineer to design and build scalable, AI-native backend services that power customer intelligence, campaign orchestration, and attribution at automotive retail scale. This role is the critical technical anchor — defining hexagonal architecture patterns, owning service boundaries, driving AI integration patterns, and setting the engineering bar for the entire team.

Key Responsibilities

 • Architect Java (Spring Boot 3.x) microservices using hexagonal architecture — defining clean domain cores, port interfaces for persistence (MongoDB, PostgreSQL, Cosmos DB), and adapter implementations for Kafka, Elasticsearch, Redis/Aerospike, and external APIs.

• Own core domain models and service boundaries end-to-end: from initial hexagonal design through production operation, Kafka event contracts, and iterative enhancement.

• Build scalable, secure REST APIs and robust Kafka-based event-driven pipelines that consume and produce events across multiple source systems. 

• Design MongoDB document schemas and PostgreSQL relational schemas for high-throughput, multi-tenant workloads — with deep attention to indexing strategy, TTL, and tenant isolation patterns.

• Design Cosmos DB data models for high-throughput event and state storage — partition key strategy, consistency levels, and TTL configuration. 

• Design and implement durable campaign execution workflows using Temporal. 

• Establish and own AI-native integration patterns: MCP tool registration, scoring model serving contracts, LLM gateway integration, and agentic workflow design.

• Identify and resolve performance bottlenecks across services, Kafka pipelines, data layers, and Elasticsearch query performance. 

• Ensure all systems meet reliability, scalability, and observability standards.

• Mentor senior, mid-level, and junior engineers — setting and consistently raising the engineering bar.

Skills & Qualifications

• 8+ years of backend engineering experience with a strong track record delivering production-grade Java systems.

• Deep expertise in hexagonal architecture (ports & adapters) — proven ability to design domain cores fully decoupled from infrastructure layers.

• Strong Java 21 and Spring Boot 3.x expertise with event-driven, microservices-first design. 

• Strong experience with Kafka — consumer groups, partition design, offset management, idempotent consumers, and event-driven service integration.

• Proven experience with MongoDB: document schema design, indexing, aggregation pipelines, and multi tenant isolation patterns.

• Strong PostgreSQL experience: complex schema design, query optimization, migration management.

• Experience with Cosmos DB or equivalent globally distributed key-value stores: partition key design, consistency tuning, high-throughput read/write patterns.

• Solid experience with Elasticsearch: index design, search query optimization, relevance tuning.

• Experience with Redis or Aerospike for high-throughput caching and session/state management.

• Strong understanding of distributed systems: service boundaries, data consistency, idempotency, retries, and circuit breaking on AWS (EKS, MSK).

Preferred Skills

• Experience with Temporal for durable workflow orchestration. 

• Familiarity with MCP tool registration patterns and agentic platform integration.

• Working knowledge of Python for AI/ML pipeline integration (scoring models, feature serving, LLM gateway patterns).

• Prior experience building data platforms, real-time analytics systems, or AI-native SaaS products.

Perks & Benefits 

• Competitive compensation and generous stock options.

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

Role Overview

We are seeking a Principal Applied Scientist to be the highest-level AI technical authority on the team. This role is above the Applied Scientist level — you set the AI research and engineering direction, own the agentic system architecture, define the eval framework standards, and operate as the primary interface to the external AI research community and internal platform AI leadership. You will combine deep research rigor with relentless production focus: every AI capability you design ships, gets measured, and improves based on evidence.

You are the person who answers: "Is this AI approach the right one, and how do we know when it's working"

Key Responsibilities

• Own the agentic system architecture: define the multi-agent coordination patterns, MCP tool taxonomy, intent-to-skill routing logic, policy enforcement design, and memory management strategy across all AI workflows on the platform.
• Lead the AI evaluation framework: design the golden dataset structure, define eval metrics (RAG retrieval quality, scoring accuracy, LLM response correctness, agentic workflow success rate), and own the CI/CD AI eval pipeline that gates every AI capability release.
• Drive the RAG architecture strategy: chunking strategies for MongoDB and Elasticsearch-indexed documents, embedding model selection and fine-tuning, retrieval reranking design, and hallucination mitigation patterns.
• Own the LLM integration architecture: prompt engineering standards, LLM gateway usage policies, context window management, streaming response patterns, and model version governance.
• Lead applied research initiatives: identify novel techniques (RLHF, Constitutional AI, multi-modal, sparse retrieval) that are practically applicable to automotive retail intelligence use cases and prototype them rigorously in Python.
• Define the hexagonal AI adapter contract standard: the formal interface specification between Python AI services and Java domain cores — ensuring AI infrastructure remains swappable without domain logic changes.
• Act as primary technical interface to platform AI leadership (LLM Gateway, ML Platform, Agentic Engine) — influencing platform roadmap based on teams practical requirements.
• Mentor the Applied Scientist and ML Architect; conduct technical reviews of AI system designs, eval frameworks, and research approaches.
• Publish, present, or contribute to open-source where appropriate — representing Tekion's AI engineering excellence externally.

Skills & Qualifications

• 10+ years of applied AI/ML experience with at least 3 years at Staff or Principal level — a track record of shipping AI systems that measurably changed business outcomes.
• Deep expertise across: LLM fine-tuning and alignment, RAG system design (chunking, embedding, retrieval, reranking), agentic frameworks (LangGraph, CrewAI, AutoGen), and MCP tool design.
• Python mastery: PyTorch, Hugging Face Transformers, LangChain/LangGraph, scikit-learn, and production ML serving tooling.
• Strong understanding of distributed AI systems: Elasticsearch-backed vector search, Redis/Aerospike serving, Cosmos DB for AI event logging, and Kafka-based feature pipelines.
• Proven ability to design formal eval frameworks for AI systems — not just accuracy metrics but business aligned quality gates.
• Experience defining and enforcing hexagonal adapter contracts between AI services and domain service layers in production systems.
• Track record of communicating complex AI system design to non-technical stakeholders, influencing product roadmaps, and driving cross-team alignment. 

Good to Have

• Publications or significant open-source contributions in NLP, information retrieval, or agentic systems.
• Experience with Constitutional AI, RLAIF, or preference optimization techniques (DPO, PPO).
• Familiarity with multi-modal AI and its application to automotive retail data (images, documents, tabular data fusion).
• Prior experience in a product-focused AI role at a SaaS or platform company — not purely research. 

Perks & Benefits

• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

About the Role

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it’s medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable.

Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity.

As a Senior Customer Engineer, you own the technical customer relationship end to end. You run discovery independently, design integration and agentic workflow architectures for complex enterprise problems, and deploy solutions live with customers — often before they know exactly how to articulate what they need. You write optimized, production-grade code at speed, grounded in strong data structures and algorithms fundamentals, because compressing the time from customer problem to working solution is how FDE delivers its value. You bring genuine innovation to hard problems — your solutions are technically sound, elegant, and often non-obvious. You are the primary technical contact for 2–4 major enterprise accounts, you mentor FDEs on the team, and you are building the skills that will take you into Staff-level technical leadership.

What You'll Do

• Own complex integration and AI agent implementations end-to-end — from technical discovery through go-live and post-launch enhancement — as the primary technical contact for 2–4 enterprise accounts
• Design integration architectures with explicit attention to error handling, retry logic, observability, failure recovery, and multi-system authentication
• Design and deploy agentic AI workflows that orchestrate supply chain operations — from requirements through production, including regression testing and validation before each customer deployment
• Deploy AI agent workflows live with customers present — configuring and troubleshooting in the room during customer calls, not gathering requirements to build later
• Run customer discovery sessions independently — hear a business problem and propose a technically credible, innovative solution on the spot without IM or management support
• Use Claude, OpenAI, and other LLMs across the entire workflow — capturing requirements, designing integrations, generating integration specs, writing code, testing and deployment; the expectation is LLM-assisted work at every stage, not just at the keyboard
• Represent FourKites from a technical lens during presales engagements — articulate integration architecture, agentic workflow capabilities, and platform extensibility to prospective enterprise customers alongside the Solutions and Sales teams
• Join scoping and strategic customer calls alongside the SCA team to tackle the highest-complexity technical and product questions — come in with a point of view, not just answers
• Perform code reviews on integration and AI workflow work from FDEs and enforce quality standards before deployment
• Mentor FDEs — pair on hard problems, review their work consistently, and take accountability for their growth
• Identify reusable integration patterns and AI workflow templates and formalize them for the team library
• Scope and estimate level of effort for projects accurately and hold yourself accountable to those estimates
• Collaborate with Implementation Managers, Customer Success Managers, Solutions Consultants, Product Managers, and Engineering to deliver seamless customer outcomes
  
  

What We're Looking For

• 5–8 years of software engineering experience, with meaningful depth in integration engineering, system design, or a customer-facing technical role — what matters is the complexity and ownership of what you have built
• Strong proficiency in Java (required) and one or more of: Python or Ruby - writes clean, production-grade code with test coverage, clear design rationale, and a standard other engineers can follow
• Strong foundations in data structures and algorithms — designs systems that perform at scale, reasons about complexity tradeoffs under pressure, and makes the right architectural call for high-throughput, low-latency integration scenarios
• Strong software design skills — architects integration and AI workflow systems that are modular, resilient, observable, and built to evolve; can articulate the design, defend the tradeoffs, and produce a diagram that makes it legible to others
• Writes optimized code at speed — takes a customer problem from discovery to deployed solution faster than traditional development cycles; the ability to compress the build cycle without compromising quality is what enables customers to move faster
• Innovative problem solver — brings genuine creativity to hard integration and AI workflow challenges; finds approaches that are technically sound, elegant, and often non-obvious; complexity doesn't slow you down, it sharpens your thinking
• Deep expertise in enterprise integration patterns and how to apply them across complex, multi-system — knows when to apply which approach and can justify the tradeoffs
• Hands-on experience designing and deploying agentic AI workflows end-to-end using LangGraph or equivalent — not configuring templates, architecting systems
• Uses Claude, OpenAI, or equivalent LLMs across the full workflow — requirements documentation, integration design, spec generation, code generation, testing and deployment; treats LLMs as a core engineering capability, not a productivity shortcut
• Proven ability to run technical discovery sessions with enterprise customers independently and translate ambiguous business requirements into concrete technical specs
• Comfortable deploying agentic workflows live in a customer call — handles configuration, troubleshooting, and edge cases in the moment
• Strong SQL proficiency — writes queries to investigate customer data issues and validate integration output

Preferred Qualifications

• Experience in supply chain, logistics, transportation, or B2B SaaS platforms is a strong plus
• Deep familiarity with enterprise integration patterns and a track record of applying them to complex, multi-system enterprise environments
• Familiarity with EDI standards, carrier integrations, TMS/WMS systems, and supply chain data flows
• Experience with low-code/no-code workflow automation platforms such as Pipedream, n8n, Temporal, or equivalent
• Snowflake experience and familiarity with large-scale data investigation across multi-tenant environments
• Proficient with Lucidchart, Miro, draw.io, or similar tools to document and communicate integration architectures and agentic workflow designs visually — customers and internal stakeholders should be able to read your design without needing to ask what it means

Background working in a Forward Deployment, Field Engineering, or similar customer-embedded technical role


Who we are:

FourKites®, the leader in AI-driven supply chain transformation for global enterprises and pioneer of advanced real-time visibility, turns supply chain data into automated action. FourKites’ Intelligent Control Tower™ breaks down enterprise silos by creating a real-time digital twin of orders, shipments, inventory and assets. This comprehensive view, combined with AI-powered digital workers, enables companies to prevent disruptions, automate routine tasks, and optimize performance across their supply chain. FourKites processes over 3.2 million supply chain events daily — from purchase orders to final delivery — helping 1,600+ global brands prevent disruptions, make faster decisions and move from reactive tracking to proactive supply chain orchestration.

FourKites provides competitive compensation with stock options, outstanding benefits and a collaborative culture for all employees around the globe. To help you be your best, we have 5 global recharge days, in addition to generous PTO and standard holidays. Parental leave for all parents, an annual wellness stipend and volunteer days also provide you with time and resources for self care and to care for others. Throughout the year, FourKites sets aside time during the workday to learn and celebrate diversity. We're always listening for new ways to support everyone in and out of the office. 

Benefits

• Medical  benefits start on first day of employment
• 36 PTO days( Sick, Casual and Earned) , 5 recharge days, 2 volunteer days 
• Home Office set ups and Technology reimbursement
• Lifestyle & Family benefits 
• Mental Wellness support and guidance 
• Ongoing learning & development opportunities ( Professional development program, Toast Master club etc.)

FourKites is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Role: GenAI Lead Engineer

Experience: 8+ years total (with significant hands-on GenAI / LLM work)

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
• Lead the end-to-end design and implementation of Generative AI solutions.
• Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
• Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
• Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
• Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
• Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
• Ensure scalability, performance, and security of AI solutions deployed in production.
• Integration and Deployment:
• API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
• Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
• Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
• Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
• Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
• Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
• Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
• Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
• Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
• Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Technical Skills:
• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
• Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
• Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
• Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
• Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
• Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
• Proven track record of leading AI projects from inception to production.
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
• Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).

Job Description : 

• 10+ years in Software / Data / ML engineering, including 3+ years in AI/ML, and 2+ years specifically in LLM / GenAI projects.
• Proven experience as a Tech Lead / Architect leading engineering teams or projects.
• Deep hands-on experience with: LLM APIs (OpenAI, Azure OpenAI, or equivalent).
• RAG architectures, embeddings, and vector databases (e.g., Pinecone, FAISS, Chroma, Qdrant, Azure AI Search).
• One or more orchestration frameworks (LangChain, Semantic Kernel, Microsoft Agent Framework, LangGraph, Copilot Studio, etc.)..
• Strong Python skills (plus experience with Node.js / C# is a bonus).
• Experience building cloud-based backend services (FastAPI, Flask, .NET, Node) and integrating with enterprise systems.
• Excellent communication skills and a track record of making architecture decisions and driving them to execution.
• Experience in Azure or AWS or GCP (GenAI Services)

Job Description: 

• 10+ years in Software / Data / ML engineering, including 3+ years in AI/ML, and 2+ years specifically in LLM / GenAI projects.
• Proven experience as a Tech Lead / Architect leading engineering teams or projects.
• Deep hands-on experience with: LLM APIs (OpenAI, Azure OpenAI, or equivalent).
• RAG architectures, embeddings, and vector databases (e.g., Pinecone, FAISS, Chroma, Qdrant, Azure AI Search).
• One or more orchestration frameworks (LangChain, Semantic Kernel, Microsoft Agent Framework, LangGraph, Copilot Studio, etc.)..
• Strong Python skills (plus experience with Node.js / C# is a bonus).
• Experience building cloud-based backend services (FastAPI, Flask, .NET, Node) and integrating with enterprise systems.
• Excellent communication skills and a track record of making architecture decisions and driving them to execution.
• Experience in Azure or AWS or GCP (GenAI Services)

Job Overview:

We are seeking an experienced Senior Data Engineer to build and optimize scalable data platforms using Microsoft Fabric, Databricks (and/or Snowflake). The role focuses on designing reliable data pipelines, lakehouse and warehouse models, and semantic layers that enable enterprise analytics, BI, and AI/Gen AI use cases.

You will work closely with analytics, BI, and data science teams to deliver high-quality, performant, and governed data solutions, while driving best practices in data engineering, optimization, and platform design.

Key Responsibilities

• Design, build, and maintain end-to-end data solutions on Microsoft Fabric, Databricks, including Pipelines, Notebooks, Lakehouse, Data Warehouse, and Semantic Models.
• Implement scalable data ingestion, transformation, and loading (ETL/ELT) using Fabric Pipelines and PySpark.
• Develop robust data models and schemas optimized for analytics, reporting, and AI-driven consumption.
• Create and maintain semantic models to support Power BI and enterprise BI solutions.
• Engineer high-performance data solutions that meet requirements for throughput, scalability, quality, and security.
• Author efficient PySpark and SQL code for large-scale data transformation, data quality management, and business rule processing.
• Build reusable framework components for metadata-driven pipelines and automation.
• Optimize Lakehouse and Data Warehouse performance, including partitioning, indexing, Delta optimization, and compute tuning.
• Develop and maintain stored procedures and advanced SQL logic for operational workloads.
• Design and prepare feature-ready datasets for AI and GenAI applications.
• Collaborate with data scientists and ML engineers to productionize AI pipelines.
• Implement data governance and metadata practices required for responsible AI.
• Leverage Fabric, Databricks capabilities to orchestrate and monitor AI-related data workflows.
• Apply data governance, privacy, and security standards across all engineered assets.
• Implement monitoring, alerting, and observability best practices for pipelines and compute workloads.
• Drive data quality initiatives, including validation frameworks, profiling, and anomaly detection.
• Partner with analytics, BI, data science, and product teams to understand requirements and translate them into technical solutions.
• Mentor junior engineers and contribute to engineering standards and patterns.
• Participate in architecture reviews, technical design sessions, and roadmap planning.
• Develop and deliver dashboards and reports using Power BI and Tableau.

Required Skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
• 7+ years of professional experience in data engineering or a related discipline.
• Mandatory hands-on expertise with Microsoft Fabric, Databricks or Snowflake including:
  • Pipelines
  • Notebooks
  • Lakehouse
  •  Data Warehouse
  • Semantic Models
• Advanced proficiency in PySpark for distributed data processing.
• Strong command of SQL for analytical and operational workloads.
• Experience developing and optimizing stored procedures and complex SQL transformations.
• Understanding of GenAI architectures, vectorization, embedding pipelines, and data preparation for LLM use cases.
• Strong knowledge of data modeling, ETL/ELT patterns, and modern data lakehouse principles.
• Experience designing and optimizing large-scale data pipelines in cloud environments (Azure preferred).
• Excellent problem-solving skills with the ability to analyze complex data workflows.
• Proficiency in creating interactive dashboards and reports using Power BI and Tableau.

Job Description

We are looking for a Senior QA Engineer / SDET to drive quality across our AI-native backend services and platform systems. You will own test automation strategy, release quality gates, and quality engineering practices — working closely with backend engineers (Java + Python), product managers, and platform architects. This role focuses heavily on validating hexagonal architecture adapters, Kafka event pipelines, multi-database correctness, and AI scoring model outputs.

Key Responsibilities

• Design, build, and scale automated test frameworks for Java microservices built on hexagonal architecture — with distinct test strategies for the domain core, adapter layers (MongoDB, PostgreSQL, Cosmos DB, Kafka, Elasticsearch, Redis/Aerospike), and external integrations.

• Develop and maintain comprehensive test suites: functional, integration (Testcontainers), regression, contract, and end-to-end across all adapter implementations.

• Validate Kafka event pipelines: consumer behavior, event ordering, idempotency, poison pill handling, and dead-letter queue processing. 

• Validate MongoDB document integrity, PostgreSQL relational consistency, Cosmos DB partition correctness, and Elasticsearch index accuracy across service boundaries.

• Design and execute golden dataset test scenarios — seeding realistic dealer and customer data to validate scoring accuracy, suppression correctness, and attribution logic.

• Validate Python-based AI/ML service outputs: scoring model results, recommendation correctness, and LLM response safety gates. 

• Collaborate closely with backend engineers and architects to embed quality early in hexagonal domain design and adapter implementation.

• Drive testability improvements by influencing API design, logging, observability, and error handling.

• Own release quality and go/no-go decisions by defining and tracking quality gates in CI/CD pipelines.

• Define and monitor quality metrics: test coverage, defect leakage, flakiness, MTTR, and automation ROI. 

• Lead root cause analysis for production issues and drive preventive measures.

• Mentor junior QA/SDET engineers and set best practices across teams.

Skills & Experience

• 6+ years of hands-on experience in QA Engineering, Test Automation, or SDET roles.

• Strong test automation expertise using modern Java-based frameworks; working knowledge of Python test frameworks (pytest) is a strong plus.

• Deep experience testing distributed microservices, REST APIs, and Kafka-based architectures.

• Experience with Testcontainers for integration testing across MongoDB, PostgreSQL, Kafka, and Elasticsearch locally.

• Strong understanding of Kafka testing: consumer behavior, event ordering guarantees, and idempotency validation.

• Experience with MongoDB and PostgreSQL testing patterns: data integrity, schema migration validation, multi-tenant isolation verification.

• Familiarity with Elasticsearch test strategies: index correctness, relevance, and query result validation.

• Experience with CI/CD pipeline integration (GitHub Actions, Jenkins, or equivalent).

• Familiarity with containerized environments (Docker, Kubernetes).

• Excellent problem-solving, communication, and collaboration skills.

Preferred Skills

• Experience validating AI/ML model outputs and scoring pipeline correctness.

• Exposure to contract testing (Pact or similar) and service virtualization for hexagonal adapter boundaries.

• Experience with performance, load, and chaos testing (JMeter, Gatling, k6) against Elasticsearch and Kafka.

• Background in DevOps or Site Reliability Engineering practices.

Perks & Benefits

• Competitive compensation and generous stock options. 

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies. 

Job Description

We are seeking a Staff SDET to own the quality architecture for our AI-native platform. This is not a test execution role — it is a quality engineering leadership role. You will design and own the test strategy across all layers of the hexagonal architecture (domain core, adapters, integration, end-to-end), establish quality gates for AI model outputs, build the golden dataset evaluation framework, and set the engineering bar for Senior SDETs and QA engineers on both Scrum teams. Nothing ships without your sign-off.

Key Responsibilities

• Own the complete quality architecture: define test strategies at each hexagonal layer — domain core unit tests, adapter integration tests (Testcontainers), service-to-service contract tests (Pact), and end-to-end scenario tests.

• Design and build the golden dataset evaluation framework: seed realistic multi-tenant dealer/customer data across MongoDB, PostgreSQL, Cosmos DB, Elasticsearch, and Kafka, and define assertion criteria for scoring accuracy, suppression correctness, and attribution logic. 

• Establish AI quality gates: define evaluation criteria for ML model outputs (scoring, recommendations), LLM response quality, RAG retrieval accuracy (precision@k, recall), and agentic workflow correctness.

• Architect test infrastructure: Testcontainers configurations for MongoDB, PostgreSQL, Cosmos DB, Kafka, Elasticsearch, and Redis/Aerospike — enabling fully local integration test runs.

• Own CI/CD quality pipeline: define what automated tests run at commit, PR, staging, and pre-release gates — with blocking quality thresholds.

• Define and track quality metrics: test coverage per hexagonal layer, defect leakage, flakiness rate, MTTR, and automation ROI.

• Lead root cause analysis for production escapes — own post-mortems and preventive measure implementation. 

• Mentor Senior SDETs and QA engineers across both teams; conduct design reviews for test frameworks and golden dataset designs.

• Influence backend and frontend engineers on testability: drive API design, logging, observability, and error handling that makes services intrinsically testable. 

Skills & Experience

• 8+ years of QA Engineering, Test Automation, or SDET experience with strong hands-on engineering depth.

• Deep expertise designing test strategies for hexagonal architecture: proven ability to test domain cores independently from adapters, and adapters independently from each other.

• Strong programming skills in Java (primary) and Python — able to write production-quality test frameworks, not just test scripts. 

• Expert-level Testcontainers experience across MongoDB, PostgreSQL, Kafka, Elasticsearch, and Redis/Aerospike. 

• Experience with contract testing (Pact or similar) for service boundary validation and service virtualization.

• Deep Kafka testing expertise: consumer group behavior, event ordering guarantees, idempotency, and dead-letter queue validation.

• Experience designing golden dataset strategies: multi-tenant data seeding, realistic event sequences, and deterministic assertion design.

• Experience integrating quality gates into CI/CD pipelines with meaningful blocking thresholds.

• Strong understanding of AI/ML output validation: scoring correctness, RAG retrieval quality metrics, and agentic workflow eval design.

Preferred Skills

• Experience with performance, load, and chaos testing (Gatling, k6) against Kafka, Elasticsearch, and MongoDB at scale.

• Background in AI/ML quality engineering: eval frameworks (RAGAS or similar), model regression detection, and LLM safety testing.

• Prior experience owning quality for a platform serving multiple engineering teams (quality platform ownership).

• Familiarity with Cosmos DB testing patterns and eventual consistency validation strategies.

Perks & Benefits

• Competitive compensation and generous stock options.

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

As a Lead Automation QA Engineer, you will champion world-class software quality by architecting and executing advanced, hands-on automation across complex business workflows. Though you may provide strategy and mentorship, your core focus will be as a technical individual contributor running sophisticated, E2E test automation—including data, API, mobile, and cross-platform business process validations spanning the full Lead-to-Cash cycle (Salesforce, Implementation, and NetSuite). You’ll also adopt AI-based test automation, including LLM and RAG system validations.

Responsibilities

Hands-On Test Automation:

• E2E Business Process Validation:
• Design and execute automated E2E tests spanning the full Lead-to-Cash cycle, including Salesforce, downstream processes, and financial handoff to NetSuite.
• Orchestrate multi-system test scenarios to validate data flows, business process logic, integrations, and error handling across Salesforce and NetSuite.
• Develop automated test scripts to ensure synchronization and data integrity between CRM, integrated system, and ERP for business-critical workflows.
• Data Validation:
• Write and automate SQL queries for multi-source data verification, ensuring consistent, accurate information across connected systems.
• Perform automated backend checks as opportunities progress through different pipeline stages from Lead to Revenue realization.
• API & Integration Testing:
• Build and maintain robust API validation suites using Rest Assured or similar frameworks, covering all RESTful interfaces connecting Salesforce, Integrated system, and NetSuite.
• Validate integration points and data exchange between systems.
• Mobile Test Automation:
• Create and execute automated mobile tests (Appium, Espresso, XCUITest) for mobile components of business processes (if applicable).
• AI-Driven QA:
• Leverage AI-powered test automation tools and approaches to optimize and expand test coverage.
• Design and manage automated validation of Large Language Model (LLM) or Retrieval-Augmented Generation (RAG)-enabled workflows.
• DevOps Integration:
• Integrate automated E2E and component tests into CI/CD pipelines for continuous validation.

QA Leadership:

• Mentor team members in test strategy for multi-system, E2E automation.
• Review test plans and ensure adoption of QA best practices for cross-platform business process validation.
• Collaborate with cross-functional teams (Salesforce admins, implementation engineers, ERP developers) to ensure quality across business processes.

Requirements

• 8+ years’ automation QA experience, with proven E2E validation across business process systems.
• Hands-on experience automating tests across Salesforce, middleware/implementation platforms, and ERP systems like NetSuite.
• Advanced SQL query skills for backend data validation and reconciliation.
• Strong experience with API automation (Rest Assured or similar) and automated UI testing tools.
• Experience with mobile automation frameworks (Appium, Espresso, XCUITest, etc.).
• Familiarity or experience with AI/LLM/RAG or willingness to learn and implement.
• Proficient with CI/CD, Agile workflows, and test automation best practices.
• Excellent analytical, troubleshooting, and communication skills.

About the Role

We are looking for a Full-Stack Developer to maintain, extend, and improve our SaaS risk management platform. The application helps teams map, analyse, and share risk. You will own feature development end-to-end — from database queries through to polished UI — and contribute to a clean, well-structured codebase.

What You Will Work On

The platform is a modern TypeScript / Next.js full-stack SaaS application consisting of:

• React-based frontend with Tailwind CSS and a component library for rich, polished UI
• Server-side rendering and API routes via Next.js (v14/15), including server actions
• SQL Server database with stored procedures for robust, performant data access
• LLM API integrations delivering AI-powered risk analysis features
• Auth.js authentication with multiple OAuth providers (Google, GitHub, Microsoft)
• Paddle-powered subscription and billing management

Key Technologies

Responsibilities

• Develop and maintain features across the full stack of the JS/TS application
• Build and update UI components using Tailwind CSS and the component library
• Write and optimise SQL Server queries and database access scripts
• Integrate and maintain AI-powered features via LLM APIs
• Manage authentication flows using Auth.js with OAuth providers (Google, GitHub, Microsoft)
• Maintain and extend the billing and subscription system
• Monitor application health and diagnose issues using Azure Application Insights

Required Skills & Experience

Core

• 6+ years of professional experience as a full-stack developer.
• Strong TypeScript and React proficiency
• Hands-on experience with Next.js (v14/15)
• Working knowledge of SQL Server and stored procedures

Frontend

• Tailwind CSS and component library experience
• Familiarity with SWR for client-side data fetching

Backend / Infrastructure

• Experience with server actions and API routes in Next.js
• Understanding of OAuth flows

Tooling

• Git-based team workflows (feature branches, PRs)
• Vitest / Testing Library or equivalent unit/component testing experience
• Prettier and ESLint configuration

Nice to Have

• Familiarity with LLM SDKs
• Experience with Paddle or other subscription billing platforms
• Experience with Azure

Job Description

We are looking for a Senior QA Engineer / SDET to drive quality across our AI-native backend services and platform systems. You will own test automation strategy, release quality gates, and quality engineering practices — working closely with backend engineers (Java + Python), product managers, and platform architects. This role focuses heavily on validating hexagonal architecture adapters, Kafka event pipelines, multi-database correctness, and AI scoring model outputs.

Key Responsibilities

• Design, build, and scale automated test frameworks for Java microservices built on hexagonal architecture — with distinct test strategies for the domain core, adapter layers (MongoDB, PostgreSQL, Cosmos DB, Kafka, Elasticsearch, Redis/Aerospike), and external integrations.

• Develop and maintain comprehensive test suites: functional, integration (Testcontainers), regression, contract, and end-to-end across all adapter implementations.

• Validate Kafka event pipelines: consumer behavior, event ordering, idempotency, poison pill handling, and dead-letter queue processing. 

• Validate MongoDB document integrity, PostgreSQL relational consistency, Cosmos DB partition correctness, and Elasticsearch index accuracy across service boundaries.

• Design and execute golden dataset test scenarios — seeding realistic dealer and customer data to validate scoring accuracy, suppression correctness, and attribution logic.

• Validate Python-based AI/ML service outputs: scoring model results, recommendation correctness, and LLM response safety gates. 

• Collaborate closely with backend engineers and architects to embed quality early in hexagonal domain design and adapter implementation.

• Drive testability improvements by influencing API design, logging, observability, and error handling.

• Own release quality and go/no-go decisions by defining and tracking quality gates in CI/CD pipelines.

• Define and monitor quality metrics: test coverage, defect leakage, flakiness, MTTR, and automation ROI. 

• Lead root cause analysis for production issues and drive preventive measures.

• Mentor junior QA/SDET engineers and set best practices across teams.

Skills & Experience

• 6+ years of hands-on experience in QA Engineering, Test Automation, or SDET roles.

• Strong test automation expertise using modern Java-based frameworks; working knowledge of Python test frameworks (pytest) is a strong plus.

• Deep experience testing distributed microservices, REST APIs, and Kafka-based architectures.

• Experience with Testcontainers for integration testing across MongoDB, PostgreSQL, Kafka, and Elasticsearch locally.

• Strong understanding of Kafka testing: consumer behavior, event ordering guarantees, and idempotency validation.

• Experience with MongoDB and PostgreSQL testing patterns: data integrity, schema migration validation, multi-tenant isolation verification.

• Familiarity with Elasticsearch test strategies: index correctness, relevance, and query result validation.

• Experience with CI/CD pipeline integration (GitHub Actions, Jenkins, or equivalent).

• Familiarity with containerized environments (Docker, Kubernetes).

• Excellent problem-solving, communication, and collaboration skills.

Preferred Skills

• Experience validating AI/ML model outputs and scoring pipeline correctness.

• Exposure to contract testing (Pact or similar) and service virtualization for hexagonal adapter boundaries.

• Experience with performance, load, and chaos testing (JMeter, Gatling, k6) against Elasticsearch and Kafka.

• Background in DevOps or Site Reliability Engineering practices.

Perks & Benefits

• Competitive compensation and generous stock options. 

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.