Certa

About Certa

 Certa is a leading innovator in the no-code SaaS workflow space, powering the full lifecycle for suppliers, partners, and third parties. From onboarding and risk assessment to contract management and ongoing monitoring, Certa enables businesses with automation, collaborative workflows, and continuously updated insights. Join us in our mission to revolutionize third-party management!

What You'll Do

• Partner closely with Customer Success Managers to understand client workflows, identify quality gaps, and ensure smooth solution delivery.
• Design, implement, and execute both manual and automated tests for client-facing workflows across our web platform.
• Write robust and maintainable test scripts using Python (Selenium) to validate workflows, integrations, and configurations.
• Own test planning for client-specific features, including writing clear test cases and sanity scenarios — even in the absence of detailed specs.
• Collaborate with Product, Engineering, and Customer Success teams to reproduce client-reported issues, root-cause them, and verify fixes.
• Lead or contribute to exploratory testing, regression cycles, and release validations before client rollouts.
• Proactively identify gaps, edge cases, and risks in client implementations and communicate them effectively to stakeholders.
• Act as a client-facing QA representative during solution validation, ensuring confidence in delivery and post-deployment success.

What We're Looking For

• 3–5 years of experience in Software QA (manual + automation), ideally with exposure to client-facing or Customer Success workflows.
• Strong understanding of core QA principles (priority vs. severity, regression vs. sanity, risk-based testing).
• Hands-on experience writing automation test scripts with Python (Selenium).
• Experience with modern automation frameworks (Playwright + TypeScript or equivalent) is a strong plus.
• Familiarity with SaaS workflows, integrations, or APIs (JSON, REST, etc.).
• Excellent communication skills — able to interface directly with clients, translate feedback into testable requirements, and clearly articulate risks/solutions.
• Proactive, curious, and comfortable navigating ambiguity when working on client-specific use cases.

Good to Have

• Previous experience in a Customer Success, Professional Services, or client-facing QA role.
• Experience with CI/CD pipelines, BDD/TDD frameworks, and test data management.
• Knowledge of security testing, performance testing, or accessibility testing.
• Familiarity with no-code platforms or workflow automation tools.

Perks

• Best-in-class compensation
• Fully remote work
• Flexible schedules
• Engineering-first, high-ownership culture
• Massive learning and growth opportunities
• Paid vacation, comprehensive health coverage, maternity leave
• Yearly offsite, quarterly hacker house
• Workstation setup allowance
• Latest tech tools and hardware
• A collaborative and high-trust team environment

Certa (getcerta.com) is a Silicon Valley-based startup automating the vendor, supplier, and stakeholder onboarding processes for businesses globally. Serving Fortune 500 and Fortune 1000 clients, Certa's engineering team tackles expansive and deeply technical challenges, driving innovation in business processes across industries.

Location: Remote (India only)

Role Overview

We are looking for an experienced and innovative AI Engineer to join our team and push the boundaries of large language model (LLM) technology to drive significant impact in our products and services . In this role, you will leverage your strong software engineering skills (particularly in Python and cloud-based backend systems) and your hands-on experience with cutting-edge AI (LLMs, prompt engineering, Retrieval-Augmented Generation, etc.) to build intelligent features for enterprise (B2B SaaS). As an AI Engineer on our team, you will design and deploy AI-driven solutions (such as LLM-powered agents and context-aware systems) from prototype to production, iterating quickly and staying up-to-date with the latest developments in the AI space . This is a unique opportunity to be at the forefront of a new class of engineering roles that blend robust backend system design with state-of-the-art AI integration, shaping the future of user experiences in our domain.

Key Responsibilities

• Design and Develop AI Features: Lead the design, development, and deployment of generative AI capabilities and LLM-powered services that deliver engaging, human-centric user experiences . This includes building features like intelligent chatbots, AI-driven recommendations, and workflow automation into our products.
• RAG Pipeline Implementation: Design, implement, and continuously optimize end-to-end RAG (Retrieval-Augmented Generation) pipelines, including data ingestion and parsing, document chunking, vector indexing, and prompt engineering strategies to provide relevant context to LLMs . Ensure that our AI systems can efficiently retrieve and use information from knowledge bases to enhance answer accuracy.
• Build LLM-Based Agents: Develop and refine LLM-based agentic systems that can autonomously perform complex tasks or assist users in multi-step workflows. Incorporate tools for planning, memory, and context management (e.g. long-term memory stores, tool use via APIs) to extend the capabilities of our AI agents . Experiment with emerging best practices in agent design (planning algorithms, self-healing loops, etc.) to make these agents more reliable and effective.
• Integrate with Product Teams: Work closely with product managers, designers, and other engineers to integrate AI capabilities seamlessly into our products, ensuring that features align with user needs and business goals . You’ll collaborate cross-functionally to translate product requirements into AI solutions, and iterate based on feedback and testing.
• System Evaluation & Iteration: Rigorously evaluate the performance of AI models and pipelines using appropriate metrics – including accuracy/correctness, response latency, and avoidance of errors like hallucinations . Conduct thorough testing and use user feedback to drive continuous improvements in model prompts, parameters, and data processing.
• Code Quality & Best Practices: Write clean, maintainable, and testable code while following software engineering best practices . Ensure that the AI components are well-structured, scalable, and fit into our overall system architecture. Implement monitoring and logging for AI services to track performance and reliability in production.
• Mentorship and Knowledge Sharing: Provide technical guidance and mentorship to team members on best practices in generative AI development . Help educate and upskill colleagues (e.g. through code reviews, tech talks) in areas like prompt engineering, using our AI toolchain, and evaluating model outputs. Foster a culture of continuous learning and experimentation with new AI technologies.
• Research & Innovation: Continuously explore the latest advancements in AI/ML (new model releases, libraries, techniques) and assess their potential value for our products . You will have the freedom to prototype innovative solutions – for example, trying new fine-tuning methods or integrating new APIs – and bring those into our platform if they prove beneficial. Staying current with emerging research and industry trends is a key part of this role .

Required Skills and Qualifications

• Software Engineering Experience: 3+ years (Mid-level) / 5+ years (Senior) of professional software engineering experience. Rock-solid backend development skills with expertise in Python and designing scalable APIs/services. Experience building and deploying systems on AWS or similar cloud platforms is required (including familiarity with cloud infrastructure and distributed computing) . Strong system design abilities with a track record of designing robust, maintainable architectures is a must.
• LLM/AI Application Experience: Proven experience building applications that leverage large language models or generative AI. You have spent time prompting and integrating language models into real products (e.g. building chatbots, semantic search, AI assistants) and understand their behavior and failure modes . Demonstrable projects or work in LLM-powered application development – especially using techniques like RAG or building LLM-driven agents – will make you stand out .
• AI/ML Knowledge: Prioritize applied LLM product engineering over traditional ML pipelines. Strong chops in prompt design, function calling/structured outputs, tool use, context-window management, and the RAG levers that matter (document parsing/chunking, metadata, re-ranking, embedding/model selection). Make pragmatic model/provider choices (hosted vs. open) using latency, cost, context length, safety, and rate-limit trade-offs; know when simple prompting/config changes beat fine-tuning, and when lightweight adapters or fine-tuning are justified. Design evaluation that mirrors product outcomes: golden sets, automated prompt unit tests, offline checks, and online A/Bs for helpfulness/correctness/safety; track production proxies like retrieval recall and hallucination rate. Solid understanding of embeddings, tokenization, and vector search fundamentals, plus working literacy in transformers to reason about capabilities/limits. Familiarity with agent patterns (planning, tool orchestration, memory) and guardrail/safety techniques.
• Tooling & Frameworks: Hands-on experience with the AI/LLM tech stack and libraries. This includes proficiency with LLM orchestration libraries such as LangChain, LlamaIndex, etc., for building prompt pipelines . Experience working with vector databases or semantic search (e.g. Pinecone, Chroma, Milvus) to enable retrieval-augmented generation is highly desired.
• Cloud & DevOps: Own the productionization of LLM/RAG-backed services as high-availability, low-latency backends. Expertise in AWS (e.g., ECS/EKS/Lambda, API Gateway/ALB, S3, DynamoDB/Postgres, OpenSearch, SQS/SNS/Step Functions, Secrets Manager/KMS, VPC) and infrastructure-as-code (Terraform/CDK). You’re comfortable shipping stateless APIs, event-driven pipelines, and retrieval infrastructure (vector stores, caches) with strong observability (p95/p99 latency, distributed tracing, retries/circuit breakers), security (PII handling, encryption, least-privilege IAM, private networking to model endpoints), and progressive delivery (blue/green, canary, feature flags). Build prompt/config rollout workflows, manage token/cost budgets, apply caching/batching/streaming strategies, and implement graceful fallbacks across multiple model providers.
• Product and Domain Experience: Experience building enterprise (B2B SaaS) products is a strong plus . This means you understand considerations like user experience, scalability, security, and compliance. Past exposure to these types of products will help you design AI solutions that cater to a range of end-users.
• Strong Communication & Collaboration: Excellent interpersonal and communication skills, with an ability to explain complex AI concepts to non-technical stakeholders and create clarity from ambiguity . You work effectively in cross-functional teams and can coordinate with product, design, and ops teams to drive projects forward.
• Problem-Solving & Autonomy: Self-motivated and able to manage multiple priorities in a fast-paced environment . You have a demonstrated ability to troubleshoot complex systems, debug issues across the stack, and quickly prototype solutions. A “figure it out” attitude and creative approach to overcoming technical challenges are key.

Preferred (Bonus) Qualifications

• Multi-Modal and Agents: Experience developing complex agentic systems using LLMs (for example, multi-agent systems or integrating LLMs with tool networks) is a bonus . Similarly, knowledge of multi-modal AI (combining text with vision or other data) could be useful as we expand our product capabilities.
• Startup/Agile Environment: Prior experience in an early-stage startup or similarly fast-paced environment where you’ve worn multiple hats and adapted to rapid changes . This role will involve quick iteration and evolving requirements, so comfort with ambiguity and agility is valued.
• Community/Research Involvement: Active participation in the AI community (open-source contributions, research publications, or blogging about AI advancements) is appreciated. It demonstrates passion and keeps you at the cutting edge. If you have published research or have a portfolio of AI side projects, let us know !

Perks of working at Certa.ai:

• Best-in-class compensation
• Fully-remote work with flexible schedules
• Continuous learning
• Massive opportunities for growth
• Yearly offsite
• Quarterly hacker house
• Comprehensive health coverage
• Parental Leave
• Latest Tech Workstation
• Rockstar team to work with (we mean it!)

About Certa

Certa is a leading innovator in the no-code SaaS workflow space, powering the full lifecycle for suppliers, partners, and third parties. From onboarding and risk assessment to contract management and ongoing monitoring, Certa enables businesses with automation, collaborative workflows, and continuously updated insight. Join us in our mission to revolutionize third-party management!

What You'll Do

• Design, implement, and execute both manual and automated tests for our web platform, ensuring robust quality across browsers, devices, and configurations.
• Own test planning for features, including writing clear test scenarios and sanity cases — even in the absence of complete specs.
• Develop and maintain automation frameworks (Playwright + TypeScript, Momentic) to ensure scalable, reliable test coverage.
• Drive product quality by proactively identifying gaps, edge cases, and risks, and collaborating closely with Product, Engineering, and Design.
• Lead or contribute to exploratory testing, regression cycles, and release sign-offs.
• Communicate test results, risks, and recommendations effectively to stakeholders.
• Stay up to date with evolving best practices in manual, automation, and product quality strategies.

What We're Looking For

• 3-5 years of experience in software QA (manual + automation) with demonstrated ownership of testing strategies and execution.
• Strong understanding of core QA principles (priority vs. severity, testing types, risk-based testing).
• Hands-on expertise with Playwright + TypeScript or equivalent frameworks for automation.
• Familiarity with CI/CD pipelines, BDD/TDD frameworks, and test data management.
• Proven experience in collaborating with cross-functional teams to improve product quality.
• Clear communication skills — can articulate testing strategies, product risks, and technical decisions effectively.
• Curious, proactive, and comfortable asking the right questions when context is missing.

Good to Have

• Experience with no-code platforms
• Exposure to security testing, accessibility testing, or performance testing.
• Familiarity with SOLID principles, design patterns, or ACID properties in the context of automation frameworks.

Perks

• Best-in-class compensation
• Fully remote work
• Flexible schedules
• Engineering-first, high-ownership culture
• Massive learning and growth opportunities
• Paid vacation, comprehensive health coverage, maternity leave
• Yearly offsite, quarterly hacker house
• Workstation setup allowance
• Latest tech tools and hardware
• A collaborative and high-trust team environment

Certa (getcerta.com) is a Silicon Valley-based tech product start-up that is automating the vendor, supplier, and other stakeholder onboarding processes (think background checks, agreements, and the works) for companies across industries and geographies. With multiple Fortune 500 and Fortune 1000 clients, at Certa's tech team, you will be working on stuff that is changing the way huge companies do business.

Must Haves:

• Experience developing enterprise-grade quality software.
• 3+ years of experience building large-scale front-end applications using React.
• 3+ years of experience using type-safe JavaScript-based languages, such as TypeScript.
• Understanding of modern frontend ecosystems, including Bundling(preferably using vite), Linting, Testing and Releasing
• Success with mentoring mid-level & junior Engineers.
• Experience in Agile software development methodologies.
• Experience writing automated tests (e.g., Vitetest, Cypress, Jest, Testing Library).
• Experience in building, scaling & maintaining a design system from scratch.
• Experience in improving rendering as well as delivery performance for front-end applications.
• Experience in writing semantic HTML.
• Experience in building scalable, responsive, and cross-browser-compatible web applications.
• Experience in a peak-performance organization, preferably a tech startup.
• Experience working with a remote team.
• Data analysis experience, and understanding of how analytics can help with product decisions.

Bonus:

• Experience building integrations and data synchronizations with event pub/sub-models.
• Experience with WebGL
• Experience in building offline applications using Web Workers
• Open source contributions.
• Running his/her own blog.
• Experience with building 100% keyboard and screen reader-accessible applications.
• Experience setting up and customizing JavaScript tooling and building systems.