AI Engineer - Full Stack Developer at Marseer Ai · Remote only · 5 - 10 years · ₹20L - ₹30L / yr · Profitable · Remote only · Posted 14 Jun 2026
About Marseer AI
Marseer AI (www.marseerai.com) is a Seattle-based company building an AI-powered marketing intelligence platform for DTC and retail e-commerce brands. The platform combines brand strategy, customer data, automation, and generative AI to help marketing teams drive consistent, data-driven engagement across email, SMS, paid media, SEO, and affiliate channels.
Role Overview
We are looking for an experienced AI Engineer - Full Stack Developer to join the Marseer platform team. This is a dual-track role: you will build and maintain AI agent pipelines, LLM integrations, and RAG-based intelligence systems on the backend, while also owning frontend interfaces that surface insights, recommendations, and campaign outputs to marketing teams and brand operators.
You should be equally comfortable designing multi-step agentic workflows in Python and building clean, responsive product interfaces in React/Next.js. You understand how LLMs behave in production, know how to engineer prompts and tool chains for reliability, and care deeply about the end-to-end user experience.
What You Will Do
- Design and implement multi-step AI agent workflows using LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar.
- Build and maintain RAG pipelines, including chunking strategies, embedding generation, vector store management, and retrieval tuning.
- Integrate with LLM providers such as OpenAI, Anthropic, or others, including prompt engineering, tool/function calling, structured output generation, and context window management.
- Develop AI-driven features such as campaign brief generation, audience recommendations, content variant creation, and performance insight summarization.
- Implement evaluation and observability frameworks to monitor LLM output quality, latency, and cost in production.
- Build frontend interfaces using React and Next.js, including dashboards, agent interaction UIs, campaign builders, and insight surfaces.
- Design and implement RESTful and/or GraphQL APIs in Python (FastAPI or Flask) or Node.js to serve AI outputs to the frontend.
- Integrate frontend with backend AI services, streaming LLM responses, and real-time status updates.
- Work with structured and unstructured marketing data, campaign performance metrics, audience segments, content libraries, and brand strategy documents.
- Integrate with marketing platforms and data sources such as Klaviyo, Google Ads, Meta, and Shopify.
Requirements
- 5-10 years of professional software engineering experience, with meaningful time in both backend and frontend development.
- Proven experience building and deploying LLM-powered applications in production, not just prototypes.
- Strong proficiency in Python for backend and AI development.
- Strong proficiency in React and Next.js for frontend development.
- Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or equivalent.
- Experience building RAG pipelines, vector stores such as Pinecone, Weaviate, pgvector, or similar, embedding models, and retrieval strategies.
- Experience with API design, REST or GraphQL, and backend service architecture.
Strongly Preferred
- Experience designing and building multi-agent or agentic AI systems with tool use, memory, and planning capabilities.
- Familiarity with prompt engineering best practices, structured output generation, and LLM evaluation methodologies.
- Experience with streaming LLM responses and real-time UI updates using SSE or WebSockets.
- Prior work in a SaaS product company shipping production features.
- Familiarity with marketing platforms, e-commerce data, or martech ecosystems.
Good to Have
- TypeScript and modern frontend tooling such as Tailwind CSS or shadcn/ui.
- Familiarity with Snowflake or other cloud data warehouses as data sources for AI pipelines.
- Experience with observability tools for LLM applications such as LangSmith, Helicone, Arize, or similar.
- Understanding of marketing concepts such as segmentation, campaign lifecycle, attribution, and content personalization.
What We Are Looking For
- Availability to work US business hours; overlap with US Eastern or Pacific timezone is required for client collaboration and team standups.
- Strong written and verbal English communication.
- Product sense and ownership mindset.
- Comfort with ambiguity in non-deterministic LLM-powered systems.
- Collaborative working style across engineering, design, and client-facing functions.
What We Offer
- Competitive compensation based on experience.
- Fully remote role; work from anywhere in India, with Hyderabad-based candidates preferred.
- High-impact work at the frontier of applied AI for marketing and e-commerce.
- Direct exposure to real brand problems, real data, and real production AI systems.
- A small, senior team where your architecture decisions matter and your contributions are visible.

About Marseer Ai
About
Marseer AI deploys AI agents across email, paid social, SEO, affiliate, and creator marketing—so lean DTC teams can execute with enterprise-level sophistication.
Candid answers by the company
Fully remote, India based. Hyderabad Candidates preferred.
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- Python (advanced, AI applications)
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Join us to work on cutting-edge AI technology that builds the future of autonomous software.
Apply: https://processity.ai/careers/fullstack-ai-engineer
BigMantra is a Vertical Autonomous AI Agent Builder — we build AI companies that go a mile deep into specific industries. Our products include Mantra Spaces (AI-powered UK HMO property management) and Verity Law (AI-powered legal conveyancing). Our team is small, our stack is modern, and your code ships to production the same week you write it.
We're looking for a Fullstack AI Applied Engineer who can build full applications end-to-end and wire AI agents into production systems that real users depend on.
WHAT YOU'LL DO
• Build and ship full-stack web applications using React / Next.js and Python / Node.js
• Design and implement AI agent workflows using LangChain, LangGraph, Claude Agent SDK, Agno, or similar
• Integrate agents with real-world APIs — Salesforce, Google Workspace, WhatsApp Business, email providers
• Build and optimize database layers — production SQL, schema design, RAG pipelines
• Own deployment and infrastructure — Docker services, CI/CD pipelines on AWS or Azure
• Write tests that matter — E2E, load tests, performance benchmarks
• Collaborate directly with the founding team on architecture and product direction
MUST HAVE
• 3+ years of professional software engineering experience
• Strong JavaScript / TypeScript — React, Next.js, Node.js in production
• Strong Python — backends, agent systems, data pipelines
• Hands-on experience with at least one AI agent framework (LangChain, LangGraph, Claude Agent SDK, Agno, or equivalent)
• Docker services for containerization and deployment
• CI/CD pipelines — GitHub Actions, GitLab CI, or similar
• Deployment experience on AWS or Azure
• Solid SQL and database skills — schema design, query optimization
GOOD TO HAVE
• Experience with autonomous agents — MCP (Model Context Protocol), skills, plugins, tool-use
• Memory and context management for long-running agents
• Prompt engineering and optimization
COMPENSATION & BENEFITS
• ₹30L – 50L per annum (based on experience)
• Equity / ESOPs — early-stage participation
• Remote-friendly — Coimbatore office available
• Learning budget — courses, conferences, AI tooling subscriptions
• Flexible hours — output over seat time
About the Role
We are looking for a hands-on Applied AI / Full Stack Engineer to build AI-powered products and experiences. The ideal candidate should be comfortable working across AI, backend, and frontend and taking features from idea to production.
Key Responsibilities
- Build and deploy AI/LLM-powered applications and features.
- Develop AI agents, RAG pipelines, tool/function-calling workflows and integrations.
- Build scalable backend APIs and services.
- Develop frontend applications using React/Next.js.
- Integrate LLMs such as OpenAI, Claude, Gemini, etc.
- Work with databases, cloud platforms and production deployments.
- Collaborate with product and design teams and take ownership of features end-to-end.
Must-Have Skills
- 3–6 years of software engineering experience.
- Strong Python and/or TypeScript/Node.js.
- Strong React.js / Next.js / TypeScript experience.
- Hands-on experience with LLMs / Generative AI.
- Experience with RAG, AI Agents or tool/function calling.
- Experience building and deploying real-world products.
- Good understanding of APIs, databases and cloud deployment.
Good to Have
- LangChain / LangGraph / LlamaIndex
- PostgreSQL / Vector Databases
- AWS / GCP / Azure / Vercel
- Docker / CI/CD
- Experience in an early-stage startup or AI product company.
We are looking for builders who can take a problem, experiment, build, ship and improve it—not just candidates with AI keywords on their resume.
Total Experience: 4+ years
Mode of Hire: Permanent
Required Skills Set (Mandatory): HTML, JavaScript, Node.js, Express.js, MongoDB, React/Next.js, AI Integration (LLMs/APIs - OpenAI, Anthropic, Gemini)
Desired Skills (Good if you have): Cloud Platforms (AWS), System Design, Application Security
What is the role all about?
We're hiring full-stack engineers who build with AI, not the traditional way. You should be fluent in modern web engineering, primarily Node.js, and just as fluent in using LLMs and AI tools (Cursor, Claude Code, and similar) to ship fast. Work that once took a month should take a week; what took a week should take a day.
The role spans a range, from architecting backends for non-trivial products like assistants and agents, to rapidly turning a requirement into a clean, customer-facing app or MVP. Be strong in at least one area, be comfortable across the system as a whole, and tell us where you're strongest so we can place you accordingly.
What will you do?
- Plan, build, and ship product features end-to-end, with AI embedded where it has the most impact.
- Integrate LLMs and AI APIs into production-grade applications.
- Use AI tools to prototype, build, and deliver at high speed without sacrificing quality.
- Design scalable APIs and data models with Node.js, Express.js, and MongoDB.
- Build responsive, performant, customer-facing interfaces with React/Next.js.
- Contribute to design discussions, code reviews, and architectural decisions.
What are we looking for?
AI leverage:
- You've shipped real things using LLMs or AI APIs and instinctively reach for AI to move faster.
- Comfortable with prompt engineering and judging AI output for production-readiness.
Engineering depth and delivery:
- Solid fundamentals: problem-solving, data structures, and how systems fit together.
- At least 2+ years across frontend (React/Next.js), APIs (Node.js/Express.js), and databases (MongoDB).
- You write clean, production-grade code and you ship.
- Knowledge of application security or ethical hacking is an advantage.
Culture
- Work with performance-oriented teams driven by ownership and passion.
- Learn to design systems for high accuracy, efficiency, and scalability.
- No strict deadlines, focus on delivering quality work.
- Meritocracy-driven, candid culture. No politics.
- Very high visibility regarding which startups and markets are exciting globally.
About Tracxn
Tracxn (Tracxn.com) is a Bangalore-based product company that provides a research and deal-sourcing platform for Venture Capital, Private Equity, Corp Dev, and professionals in the startup ecosystem.
We are a team of 800+ working professionals serving customers across the globe. Our clients include Funds such as Andreessen Horowitz, Matrix Partners, and GGV Capital, as well as Large Corporates such as Citi, Embraer & Ferrero.
Founders
- Neha Singh (ex-Sequoia, BCG | MBA - Stanford GSB)
- Abhishek Goyal (ex-Accel Partners, Amazon | BTech - IIT Kanpur)
About Technology Team
Tracxn's Technology team is 50+ members strong and growing. The technology team is subdivided into multiple smaller teams, each of which owns one or more services/components of the technology platform. Ours is a young team of motivated engineers with a minimal management structure, in which almost everyone is actively involved in technical development and design. We have a team-centric culture where ownership and responsibility for a feature or module lie with a team rather than an individual.
We work on an array of technologies, including but not limited to ReactJS, Next.js, Storybook, Webpack, Node, Mongo, AWS Lambda, Spring, Elastic Stack, MySQL, Kafka, Redis, Ansible, etc.
We value ownership, continuous learning, consistency, and discipline as a team.
Position Overview
We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and
maintain end-to-end software solutions spanning web platforms, desktop applications, and
autonomous AI agents capable of interacting with and controlling these software systems.
The ideal candidate will bridge traditional engineering software with cutting-edge artificial
intelligence to automate data processing and enhance operational decision-making. While
not strictly required, a background or strong interest in the energy sector—specifically
drilling and completion operations—is highly desirable.
Key Responsibilities
• Full Stack Development: Design, develop, and deploy robust web applications and
native desktop software utilized by engineering and operational teams.
• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-
driven workflows capable of interpreting data, executing commands, and safely
controlling desktop and web-based software.
• Workflow Automation: Translate complex workflows into intuitive software features
and autonomous agent actions, minimizing manual data entry and operational
bottlenecks.
• Data Integration: Handle high-frequency data streams and integrate them seamlessly
into user interfaces and backend AI models.
• Architecture & Scalability: Ensure high performance, security, and scalability across
cloud infrastructure (AWS/Azure), local desktop environments, and potential edge
computing setups.
• Cross-Functional Collaboration: Work closely with domain experts and end-users to
translate field challenges into technical product requirements.
Required Qualifications & Experience
• Experience: Minimum of 5 years of professional software development experience,
with a proven track record of delivering production-ready web and desktop
applications.
• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at
least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend
frameworks (React, Angular, or Vue.js), Node.js, and desktop application development
(Electron, WPF, Qt, or Tauri).
• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs
(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,
AutoGPT, or custom agent architectures.
• Automation & UI Control: Expertise in software control mechanisms using tools like
Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to
allow AI agents to navigate software.
• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud
platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.
Preferred Qualifications (Strong Plus)
• Industry Domain Expertise: Prior hands-on development experience within the oil and
gas sector, specifically focused on drilling, completions, rig operations, or subsurface
engineering software.
• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and
time-series databases.
• Experience deploying AI models and agents in edge or low-connectivity environments
(such as offshore rigs or remote drilling sites).
• Familiarity with safety-critical software design and cybersecurity standards in
industrial control systems (ICS/SCADA).
• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.
Total Experience: 4+ years
Mode of Hire: Permanent
Required Skills Set (Mandatory): HTML, JavaScript, Node.js, Express.js, MongoDB, React/Next.js, AI Integration (LLMs/APIs - OpenAI, Anthropic, Gemini)
Desired Skills (Good if you have): Cloud Platforms (AWS), System Design, Application Security
What is the role all about?
We're hiring full-stack engineers who build with AI, not the traditional way. You should be fluent in modern web engineering, primarily Node.js, and just as fluent in using LLMs and AI tools (Cursor, Claude Code, and similar) to ship fast. Work that once took a month should take a week; what took a week should take a day.
The role spans a range, from architecting backends for non-trivial products like assistants and agents, to rapidly turning a requirement into a clean, customer-facing app or MVP. Be strong in at least one area, be comfortable across the system as a whole, and tell us where you're strongest so we can place you accordingly.
What will you do?
- Plan, build, and ship product features end-to-end, with AI embedded where it has the most impact.
- Integrate LLMs and AI APIs into production-grade applications.
- Use AI tools to prototype, build, and deliver at high speed without sacrificing quality.
- Design scalable APIs and data models with Node.js, Express.js, and MongoDB.
- Build responsive, performant, customer-facing interfaces with React/Next.js.
- Contribute to design discussions, code reviews, and architectural decisions.
What are we looking for?
AI leverage:
- You've shipped real things using LLMs or AI APIs and instinctively reach for AI to move faster.
- Comfortable with prompt engineering and judging AI output for production-readiness.
Engineering depth and delivery:
- Solid fundamentals: problem-solving, data structures, and how systems fit together.
- At least 2+ years across frontend (React/Next.js), APIs (Node.js/Express.js), and databases (MongoDB).
- You write clean, production-grade code and you ship.
- Knowledge of application security or ethical hacking is an advantage.
Culture
- Work with performance-oriented teams driven by ownership and passion.
- Learn to design systems for high accuracy, efficiency, and scalability.
- No strict deadlines, focus on delivering quality work.
- Meritocracy-driven, candid culture. No politics.
- Very high visibility regarding which startups and markets are exciting globally.
About Tracxn
Tracxn (Tracxn.com) is a Bangalore-based product company that provides a research and deal-sourcing platform for Venture Capital, Private Equity, Corp Dev, and professionals in the startup ecosystem.
We are a team of 800+ working professionals serving customers across the globe. Our clients include Funds such as Andreessen Horowitz, Matrix Partners, and GGV Capital, as well as Large Corporates such as Citi, Embraer & Ferrero.
Founders
- Neha Singh (ex-Sequoia, BCG | MBA - Stanford GSB)
- Abhishek Goyal (ex-Accel Partners, Amazon | BTech - IIT Kanpur)
About Technology Team
Tracxn's Technology team is 50+ members strong and growing. The technology team is subdivided into multiple smaller teams, each of which owns one or more services/components of the technology platform. Ours is a young team of motivated engineers with a minimal management structure, in which almost everyone is actively involved in technical development and design. We have a team-centric culture where ownership and responsibility for a feature or module lie with a team rather than an individual.
We work on an array of technologies, including but not limited to ReactJS, Next.js, Storybook, Webpack, Node, Mongo, AWS Lambda, Spring, Elastic Stack, MySQL, Kafka, Redis, Ansible, etc.
We value ownership, continuous learning, consistency, and discipline as a team.
Job Title
Python Full Stack Developer – AI
Experience: 6-9 Years
Location: Bangalore (Hybrid)
Employment Type: Full-Time
Job Summary
We are seeking a highly skilled Python Full Stack Developer with AI expertise to design, develop, and deploy scalable AI-powered applications. The ideal candidate should have strong experience in Python, Full Stack Development, REST APIs, modern frontend frameworks, and Generative AI technologies, including LLMs, prompt engineering, and AI integrations.
The role involves building end-to-end web applications, integrating AI models, and collaborating with cross-functional teams to deliver innovative AI-driven solutions.
Key Responsibilities
· Design, develop, and maintain scalable full-stack applications using Python.
· Build responsive and interactive user interfaces using React.js, Angular, or Vue.js.
· Develop backend services and RESTful APIs using Django, Flask, or FastAPI.
· Integrate Generative AI models such as OpenAI GPT, Claude, Gemini, or Llama into business applications.
· Develop AI-powered chatbots, assistants, document processing, and workflow automation solutions.
· Implement prompt engineering techniques to optimize AI model performance.
· Build Retrieval-Augmented Generation (RAG) pipelines using vector databases.
· Work with LangChain, LangGraph, or LlamaIndex for LLM orchestration.
· Integrate AI APIs and third-party services into enterprise applications.
· Design and optimize SQL and NoSQL databases.
· Deploy applications on AWS, Azure, or GCP.
· Develop CI/CD pipelines and manage deployments using Docker and Kubernetes.
· Write clean, reusable, and well-documented code following best practices.
· Participate in Agile ceremonies, code reviews, and sprint planning.
Required Technical Skills
Backend
· Python
· Django
· Flask
· FastAPI
Frontend
· React.js / Angular / Vue.js
· HTML5
· CSS3
· JavaScript (ES6+)
· TypeScript
AI / Generative AI
· OpenAI API
· Azure OpenAI
· Gemini API
· Claude API
· Llama Models
· LangChain
Databases
· PostgreSQL
· MySQL
· MongoDB
· Redis
Cloud & DevOps
· AWS / Azure / Google Cloud Platform
· Docker
· Kubernetes
· Git
· GitHub
· Jenkins
· CI/CD
API Development
· REST APIs
· GraphQL (Preferred)
· API Integration
Preferred Skills
· Machine Learning fundamentals
· NLP (Natural Language Processing)
· Hugging Face Transformers
· TensorFlow or PyTorch
· Kafka or RabbitMQ
· Elasticsearch
· Microservices Architecture
· Authentication (OAuth2, JWT)
Qualifications
· Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
· 6–9 years of experience in Python Full Stack Development.
· Hands-on experience with Generative AI and LLM-based application development.
· Experience working in Agile/Scrum environments.
Job Description:
We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.
Key Responsibilities:
- Develop and deploy GenAI and Agentic AI applications.
- Build RAG pipelines, LLM workflows, and AI agents.
- Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Implement tool calling, context retrieval, and LLM orchestration.
- Integrate AI solutions with APIs and cloud platforms.
- Work with AWS/Azure/GCP, Docker, and CI/CD.
Required Skills:
- Strong Python programming skills.
- 3+ years of GenAI/Agentic AI experience.
- RAG and LLM orchestration.
- LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
- MCP and A2A knowledge.
- Cloud, APIs, Docker, and CI/CD experience.
Preferred Experience:
Hands-on experience building and deploying production-ready AI solutions.
About LeadSquared
LeadSquared is a leading sales execution and marketing automation platform trusted by 2,000+ businesses globally, including healthcare, education, financial services, and real estate. Headquartered in Bengaluru with offices across the US, UK, UAE, and Southeast Asia, we empower sales teams to close faster, smarter, and at scale.
Our AI team is at the forefront of integrating cutting-edge large language model capabilities into enterprise workflows — building intelligent agents, copilots, and automation systems that redefine how businesses operate.
Role Overview
We are looking for a Senior AI Engineer with hands-on experience building LLM-powered agents and agentic AI systems. You will design, develop, and deploy autonomous AI pipelines that solve complex, multi-step business problems — from lead qualification and follow-up automation to intelligent CRM workflows and beyond.
This role is ideal for someone who is deeply excited about the frontier of AI, can move fast, and wants their work to directly impact millions of sales professionals worldwide.
Key Responsibilities
•
Design and build LLM-powered agentic systems using frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI to automate complex, multi-step workflows.
•
Develop and maintain Retrieval-Augmented Generation (RAG) pipelines with vector databases (Pinecone, Weaviate, Chroma, pgvector) for domain-specific knowledge grounding.
•
Build and integrate tool-use and function-calling capabilities into AI agents, enabling dynamic interaction with internal APIs, databases, and third-party services.
•
Implement prompt engineering strategies including chain-of-thought, few-shot prompting, and structured output parsing to ensure reliable agent behavior.
•
Design evaluation frameworks and observability pipelines (LangSmith, Helicone, custom metrics) to monitor agent performance, accuracy, and cost.
•
Collaborate with product, sales, and domain teams to translate business requirements into AI-driven solutions and features.
•
Optimize LLM inference for latency and cost using techniques like caching, model distillation, quantization, and batching.
•
Stay current with the rapidly evolving LLM ecosystem and proactively propose improvements and new approaches.
•
Contribute to internal best practices, documentation, and knowledge-sharing across the engineering org.
Required Qualifications
Experience
•
2–4 years of professional software engineering experience, with at least 1–2 years focused on LLM/AI systems.
•
Proven experience shipping LLM-based products or agentic AI systems into production environments.
Technical Skills
•
Strong proficiency in Python and familiarity with async programming patterns for AI pipelines.
•
Hands-on experience with LLM APIs: OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), or open-source models (Llama, Mistral).
•
Experience with agentic frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar.
•
Solid understanding of RAG architectures, embedding models, and semantic search.
•
Experience with vector databases and similarity search infrastructure.
•
Knowledge of REST APIs, microservices architecture, and containerization (Docker/Kubernetes).
Problem-Solving & Mindset
•
Strong ability to decompose ambiguous, open-ended problems into structured AI system designs.
•
Experience with prompt debugging, LLM evaluation, and iterative refinement workflows.
•
Ability to balance research exploration with engineering pragmatism to ship reliable systems.
Preferred Qualifications
•
Experience with multi-agent orchestration and agent memory systems (short-term and long-term).
•
Familiarity with fine-tuning or RLHF workflows for domain adaptation.
•
Background in NLP, information retrieval, or conversational AI.
•
Prior experience in B2B SaaS or CRM domain is a plus.
•
Contributions to open-source AI/ML projects or published research/blogs.
•
Experience with cloud platforms: AWS, GCP, or Azure — particularly AI/ML services
Job Title: Full Stack AI Engineer
Location: Remote/Hyderabad
Experience Level: 3-5
Salary Range: 12-18LPA
Application Link:https://beyond.ciltriq.com/apply/BUILD
Description:
Join a team building AI-powered systems that solve complex business problems and automate operational workflows across document processing, voice agents, enterprise integrations, workflow automation, and multi-agent systems.
Strong full-stack foundations: frontend state management, asynchronous user experiences and performance; backend API design, authentication, data modelling, databases, queues and distributed systems.
Strong coding ability in Python and JavaScript or TypeScript, with practical experience in modern frontend frameworks and backend services.
Requirements:
- Design and build complete systems: frontend applications, backend services, APIs, databases, data pipelines and integrations with customer systems.
- Build multi-agent workflows with clear agent responsibilities, tool access, shared state, context management, routing, handoffs and coordination across sequential and parallel tasks.
- Make agent execution dependable through durable state, checkpoints, retries, timeouts, idempotency, recovery and human approval or review where needed.
- Deliver document-processing pipelines, voice agents and retrieval-based AI applications, connecting model outputs to useful actions in real business workflows.
- Own quality in production: automated tests, AI evaluations, guardrails, observability, access controls, deployments, incident response and clear documentation.
- Choose where AI adds value and where deterministic software is the better fit. Balance accuracy, latency, cost, security and maintainability.
- Improve reusable engineering foundations, review code and help other engineers grow as the team expands.
- A solid understanding of tool calling, structured outputs, retrieval, context and memory management, model selection and evaluation.
- Practical cloud and deployment experience, including containers, CI/CD, secrets management, logging, monitoring and production debugging.
- Ability to reason from first principles, investigate failures across system boundaries and communicate technical decisions clearly to customers and teammates.
- Useful additional experience: Document AI and OCR, real-time voice systems, enterprise integrations, agent protocols such as MCP, and orchestration frameworks.
- Useful additional experience: Mentoring engineers or building reusable platforms.






