Full Time, On-site
Sawantwadi
Posted 2 weeks ago

1) Senior Full-Stack React Developer (4+ years)

2) Junior Full-Stack React Developer (1+ year)

3) Senior Python Developer (4+ years)

4) QA Engineer / Tester (4+ years)

1. Senior Full-Stack React Developer (4+ years)

Role summary:

This senior engineer will lead the front-end and full-stack efforts, translating UI/UX designs into functional applications using React, integrating backend services and AI-powered features, and mentoring the junior developer. The role requires a strong understanding of AI-DLC workflows and experience incorporating generative-AI capabilities into modern web applications.

Key responsibilities

  • Frontend development and UX – Design and build responsive user interfaces using React.js, HTML and CSS, translating UI/UX designs into functional code. Ensure cross-browser compatibility and optimize frontend performance.
  • Backend integration – Implement server-side logic and APIs using Python (FastAPI/Django) or Node.js, handle authentication, business logic and data processing. Develop and manage RESTful or GraphQL APIs and integrate third-party services.
  • Database design – Design efficient schemas and write queries for relational and non-relational databases (PostgreSQL, MySQL, MongoDB).
  • AI-enabled features – Integrate generative-AI functions into the product. Build chains and autonomous agents using LangChain; connect private data through LlamaIndex; implement RAG pipelines and vector databases; and expose AI services via backend APIs. Implement prompt-injection defenses and semantic guardrails to secure AI interactions.
  • Deployment and DevOps – Configure servers and deploy applications on cloud platforms (AWS, Azure or GCP). Set up continuous-integration/ continuous-deployment (CI/CD) pipelines in line with AI-DLC’s rapid cycles.
  • Testing and code quality – Write unit and integration tests, debug issues across the stack and perform code reviews. Ensure AI-generated code meets security and quality standards by reviewing AI-DLC checkpoints.
  • Collaboration and mentoring – Work closely with designers, product managers and the QA engineer; use Git for version control and Jira for tracking. Mentor the junior developer in both traditional full-stack and generative-AI practices.

Required skills and experience

  • Experience: 4+ years in full-stack development with a focus on React and Python/Node.js. Proven record of delivering production web applications.
  • Technical proficiency:
    • Strong React knowledge (hooks, component design, state management). Experience with Next.js or similar frameworks is a plus.
    • Backend development in Python (FastAPI/Django) or Node.js, with fluency in REST/GraphQL API design and database integration.
    • Familiarity with containerization (Docker) and cloud deployment (AWS/Azure/GCP).
    • Working knowledge of LangChain, LlamaIndex, vector databases and retrieval-augmented generation pipelines.
    • Proficiency with Git and CI/CD tools.
  • AI-DLC and generative AI: Understanding of the AI-Driven Development Life Cycle and ability to collaborate with AI agents during inception, construction and operations phases. Experience reviewing AI-generated code, ensuring prompt security and optimizing costs via caching and context compression.

Preferred

  • Soft skills: Excellent communication, leadership and mentoring abilities. Ability to work autonomously in a remote environment and coordinate across time zones.
  • Contributions to open-source AI tools or experience using RAG, vector databases and LLM orchestration frameworks (e.g., Autogen, AgentGPT).
  • Familiarity with application security practices and AI-DLC security recommendations.

Work environment

The senior developer will work remotely on a company-provided VM with access to cloud resources. Code will be stored in the company’s Git repository, and tasks will be managed via Jira. The role may require occasional coordination meetings during overlapping hours with the rest of the team in Asia/Kolkata.

2. Junior Full-Stack React Developer (1+ year)

Role summary:

A junior engineer who will assist in developing and testing the web application. They will work under the guidance of the senior full-stack developer to implement UI features, integrate APIs and gradually learn AI-enabled development practices.

Key responsibilities

  • UI implementation – Assist in building responsive user interfaces with React, HTML and CSS, following design specifications.
  • Component integration – Use React hooks and state management to integrate UI with backend services. Implement responsive design and cross-browser compatibility.
  • Backend support – Write simple API endpoints or extend existing ones using Python/Node.js under supervision.
  • AI-enabled tasks – Support the integration of generative-AI features by wiring up frontend interactions with AI endpoints. Learn how to use frameworks like LangChain and LlamaIndex for building chains and agents.
  • Testing and debugging – Write unit tests for components, fix bugs and participate in code reviews.
  • Collaboration – Use Git for version control and Jira to track tasks. Communicate clearly with the senior developer, QA tester and product team.

Required skills and experience

  • Experience: Minimum of 1 year working on web development projects using React.
  • Technical skills:
    • Basic proficiency in React, JavaScript/TypeScript, HTML and CSS.
    • Exposure to backend development in Python (Flask/FastAPI) or Node.js is desirable.
    • Familiarity with Git, Jira and collaborative development practices.
  • AI readiness: Willingness to learn AI frameworks such as LangChain and vector databases, and to work within AI-DLC workflows.
  • Soft skills: Eager to learn, able to take constructive feedback, strong problem-solving skills, and ability to work remotely.

Preferred

  • Experience with unit testing frameworks (e.g., Jest for React). Exposure to cloud platforms and Docker.

Work environment

The junior developer will work remotely on a VM, collaborating closely with the senior full-stack developer. They will follow tasks in Jira and commit code to Git repositories. The role offers mentorship opportunities and practical exposure to generative-AI development.

3. Senior Python Developer (4+ years)

Role summary:

This role focuses on designing and implementing backend services, data pipelines and AI integrations. The senior Python developer will collaborate with the full-stack engineers to build scalable APIs, integrate AI models and manage cloud infrastructure.

Key responsibilities

  • Clean, efficient coding – Write and maintain readable, efficient Python code and develop backend features and APIs. Use frameworks like FastAPI, Django or Flask to build web applications.
  • API and automation – Develop and document APIs that power the frontend and AI services. Create automation scripts for deployment, data processing and AI workflows.
  • Database and data handling – Design schemas and manage both SQL and NoSQL databases. Ensure secure data handling and implement ETL pipelines.
  • Generative-AI integration – Build retrieval-augmented generation pipelines, manage vector databases and orchestrate LLM calls using frameworks like LangChain and LlamaIndex. Implement asynchronous data ingestion and ensure AI outputs remain up to date.
  • MLOps and security – Monitor and maintain AI models in production, addressing issues such as data drift and prompt injection attacks. Set up semantic caching and context compression to optimize token usage and costs.
  • Testing and code quality – Perform unit and integration tests; debug and improve performance. Participate in code reviews and follow best practices.
  • Collaboration – Work closely with full-stack developers to integrate APIs and AI features. Use Git for version control and Jira for planning.

Required skills and experience

  • Experience: 4+ years in backend software development using Python.
  • Technical proficiency:
    • Expertise in Python and frameworks like FastAPI, Django or Flask.
    • Experience building RESTful/GraphQL APIs and working with microservices.
    • Solid understanding of relational and NoSQL databases; ability to optimize queries.
    • Familiarity with containerization (Docker), cloud services and CI/CD pipelines.
    • Knowledge of generative-AI tooling: LLM orchestration frameworks (LangChain/LlamaIndex), vector databases (Pinecone/FAISS), RAG pipelines and model fine-tuning techniques (PEFT, LoRA).
  • AI-DLC awareness: Ability to collaborate with AI agents during inception, construction and operations phases and to review and secure AI-generated code.
  • Soft skills: Strong analytical and problem-solving abilities; capacity to work independently in a remote setting; effective communication.

Preferred

  • Prior experience with MLOps tools (MLflow, Kubeflow) and cloud AI services (SageMaker, Vertex AI).
  • Exposure to asynchronous programming and event-driven architectures.

Work environment

The senior Python developer will work remotely on a VM with access to the organization’s AI infrastructure. They will collaborate with the front-end team and QA engineer, commit code to Git repositories and coordinate tasks through Jira.

4. QA Engineer / Tester (4+ years)

Role summary:

The QA Engineer will ensure that both traditional features and AI-enabled components meet quality, reliability and ethical standards. This role combines manual and automation testing with specialized generative-AI testing methods, requiring proficiency in QA fundamentals and an understanding of AI behaviors.

Key responsibilities

  • Quality assurance across the lifecycle – Participate early in design and development, perform both manual and automation testing, analyze user journeys and risk areas, advocate for usability and accessibility and collaborate with developers and product managers.
  • Manual testing – Conduct exploratory and regression tests, smoke and sanity checks, UI/UX validation, reproduce and report bugs and log issues in Jira.
  • Automation testing – Develop and execute automated test scripts using frameworks such as Selenium, Appium, Cypress or Playwright, and integrate tests into CI/CD pipelines. Use version control and API testing tools like Postman.
  • AI-specific QA – Perform prompt testing and input validation for generative models; evaluate AI outputs for relevance, accuracy and consistency; test for bias, toxicity and ethical issues; conduct adversarial testing to probe model robustness; run regression tests after model updates; measure performance and latency; test APIs and integrations; and validate data quality before and after training.
  • Tooling and automation – Employ AI evaluation frameworks (e.g., OpenAI Evals, DeepChecks), prompt injection checkers, LangChain testing modules and other AI-QA tools. Leverage modern QA platforms (e.g., Quash) to generate test cases and use clustering and root-cause analysis tools.
  • Collaboration within AI-DLC – Work closely with AI agents and developers to ensure AI-generated code meets security and quality standards. Support continuous automated scanning and runtime validation to bridge the gap between repository code and cloud deployment.

Required skills and experience

  • Experience: 4+ years in QA testing (manual and/or automation) within a software development environment. The role demands senior-level proficiency and the ability to mentor less-experienced team members.
  • Technical proficiency:
    • Understanding of software testing methodologies and SDLC/Agile practices.
    • Experience with test automation frameworks (Selenium, Appium, Cypress or Playwright) and API testing tools (Postman, RestAssured).
    • Ability to write scripts in Python/JavaScript, version control with Git and integrate tests into CI/CD pipelines.
    • Familiarity with AI evaluation tools, prompt testing, bias and ethical testing and adversarial testing.
  • AI-DLC awareness: Comfortable working with AI-driven workflows and understanding the unique risks associated with AI-generated code and data.
  • Soft skills: Detail-oriented, strong communication skills, ability to work cross-functionally, proactive in identifying risks and advocating for quality.

Preferred

  • Experience testing AI/ML products or chatbots. Familiarity with fairness testing tools (Perspective API, IBM Fairness 360) and vector-database testing.
  • Knowledge of security testing, including prompt injection and data privacy.

Work environment

The QA Engineer will work remotely on a VM. They will use Jira to manage test cases and Git for version control. The role will involve close coordination with developers and AI agents to maintain quality in both traditional and AI-generated features.

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