Power Platform Engineer/AI Agent Developer

Job Title : Senior Consultant – Full Stack Developer with AI

Experience : 5+ Years

Open Positions : 1

Location : Remote

Working Hours : 11:00 AM to 08:00 PM IST

Engagement : 6 to 8 Months Contract-to-Hire (C2H), with potential conversion to client payroll

Expected Joining : By the last week of August / 1st week of September

Role Overview :

Thoughtworks is looking for a Senior Consultant – Full Stack Developer with AI experience who can design and develop scalable full-stack applications while leveraging modern AI development tools and agentic AI capabilities.

The ideal candidate should have strong hands-on experience with Python, JavaScript / React.js, AWS Bedrock Agent Core, Docker, Kubernetes, and modern AI-assisted development frameworks and tools. Experience building MCP servers / tools, AI skills, or integrations using tools such as Cursor, Claude Code, Codex, or GitHub Copilot will be highly valuable.

The candidate should be comfortable working across application development, AI integration, cloud technologies, and containerized environments.

Mandatory Skills :

Python, React.js / JavaScript, AWS Bedrock Agent Core, Docker, Kubernetes, MCP / AI Skills, Cursor / Claude Code / Codex / GitHub Copilot, Full-Stack Development.

Key Responsibilities :

• Design, develop, and maintain scalable full-stack applications using modern development practices.
• Build backend services and APIs using Python and related frameworks.
• Develop responsive and scalable frontend applications using ReactJS or other JavaScript frameworks.
• Design and implement AI-powered solutions using AWS Bedrock Agent Core.
• Build and integrate AI agents, tools, skills, and workflows into enterprise applications.
• Develop and work with MCP (Model Context Protocol) servers, tools, or integrations.
• Leverage AI-assisted development platforms and coding tools such as Cursor, Claude Code, Codex, or GitHub Copilot.
• Containerize applications and services using Docker.
• Deploy, manage, and troubleshoot containerized workloads using Kubernetes.
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable technical solutions.
• Follow engineering best practices around code quality, testing, security, performance, and maintainability.
• Contribute to CI/CD and cloud deployment processes; DevOps experience will be an added advantage.
• Participate in technical discussions, architecture decisions, code reviews, and project delivery.

Mandatory Skills :

• 5+ years of relevant software development experience.
• Strong hands-on experience with Python.
• Strong experience with ReactJS or another modern JavaScript framework.
• Hands-on experience with AWS Bedrock Agent Core.
• Strong experience with Docker.
• Hands-on experience with Kubernetes.
• Experience building MCP servers / tools, AI skills, or similar AI integrations.
• Experience using AI-assisted coding/development tools such as :
• Cursor
• Claude Code
• Codex
• GitHub Copilot
• Strong understanding of full-stack application development.
• Good understanding of API development, application architecture, and cloud-based solutions.

Nice to Have :

• Experience with DevOps practices and CI/CD pipelines.
• Experience with AWS cloud services beyond Bedrock.
• Experience with infrastructure automation and deployment.
• Experience building production-grade GenAI / Agentic AI applications.
• Experience with LLM integrations, AI agents, tools, and function calling.

Project Expectations :

Candidates should be able to explain at least one recent project in detail, including :

• Problem Statement : What business / technical problem were you solving ?
• Architecture & Approach : How did you design the solution ?
• Key Contributions : What did you personally build or own ?
• AI / Agent Implementation : How did you use AWS Bedrock Agent Core, MCP, or AI development tools ?
• Technology Stack : Python, React.js / JavaScript, AWS, Docker, Kubernetes, etc.
• Challenges : What were the major technical challenges ?
• Outcomes & Metrics : What measurable impact did the solution deliver, such as performance improvement, cost reduction, automation, productivity improvement, or reduced development time ?

Interview Process :

1. Round 1 – GT Technical Interview : 60 minutes
2. Round 2 – Client Technical Interview : 60 minutes
3. Round 3 – Project Round : 60 minutes
4. Additional Client Round : May be conducted on a case-by-case basis

Key Hiring Priorities :

Highest priority : Candidates with genuine hands-on experience in AWS Bedrock Agent Core + Python + React / JavaScript + Docker + Kubernetes + MCP / AI skills and practical experience using modern AI coding/agent development tools.

Note : Candidates should demonstrate hands-on implementation experience rather than only theoretical knowledge or exposure to the above technologies.

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

Design and develop Agentic AI systems using LLMs, tools, memory,

workflows, and MCP.

Build production-grade RAG pipelines, including ingestion, chunking,

embeddings, retrieval, reranking, and evaluation.

Implement context engineering strategies for improving LLM accuracy,

relevance, and reliability.

Develop and integrate MCP-based tools and services for AI agents.

Work with LLMs, SLMs, quantized models, and model optimization

techniques for efficient inference.

Develop scalable backend services and APIs for AI applications.

Design databases and data models supporting AI/agentic applications.

Implement AI observability covering latency, token usage, cost, failures,

quality, and agent/tool execution.

Apply AI governance and responsible AI practices, including security,

access control, data privacy, and auditability.

Optimize AI systems for latency, scalability, cost, and reliability.

Collaborate with engineering and product teams to take AI solutions from

POC to production.

Strong hands-on experience with GenAI, LLMs, and Agentic AI.

Experience building RAG applications.

Strong understanding of Context Engineering and prompt/context

optimization.

Role Overview

We are looking for a hands-on AI/ML Engineer to design, develop, and deploy

production-ready GenAI and Agentic AI applications. The role involves building

intelligent agents, RAG pipelines, AI APIs, backend services, and scalable AI

infrastructure with a strong focus on context engineering, observability,

governance, and model optimisation.

Key Responsibilities

Required Skills

Practical experience with MCP (Model Context Protocol).

Experience with frameworks such as LangChain, LangGraph,

LlamaIndex, or equivalent.

Knowledge of LLM/SLM deployment and quantization techniques.

Strong Python backend development experience.

Experience developing REST APIs using FastAPI/Flask or equivalent.

Strong understanding of SQL/NoSQL databases and database design.

Experience with vector databases such as Qdrant, Pinecone, Weaviate,

ChromaDB, or FAISS.

Understanding of AI observability, evaluation, monitoring, and

governance.

Experience with cloud platforms and production deployment is preferred.

Strong understanding of software engineering principles, Git, testing, and

CI/CD.

Build AI where the work actually happens.

Celeco works inside real businesses to understand critical workflows, ship production AI systems and stay through adoption.

We are hiring our first Intelligence Architect (Forward-Deployed AI Engineer).

⌁

Full-time · Remote-first · Optional hybrid in Bengaluru

At least one year of professional engineering experience. Customer travel when the work requires it.

The role

An Intelligence Architect enters a customer environment with an unfinished question and leaves behind a working, measurable system.

This is a hands-on engineering role at the boundary of product, operations and customer delivery. You will learn the domain, inspect the existing systems and data, decide what should be built, and write the code that puts it into production.

What you will own

• Interview and shadow the people doing the work, then map the real workflow, including hand-offs, exceptions and workarounds.
• Understand the customer's application stack, APIs, data, identity model, security constraints and deployment environment.
• Turn business goals into a technical scope, system design, delivery plan and measures of success.
• Build across the stack: AI workflows, data pipelines, integrations, backend services and the interfaces people use.
• Choose the simplest reliable approach. The answer may combine agents, retrieval, rules and conventional software.
• Create evals from representative cases, define quality and failure metrics, inspect traces, red-team the system and set launch thresholds.
• Make practical trade-offs across accuracy, latency, cost, privacy, security and speed.
• Take prototypes into production with tests, monitoring, access controls, documentation and a plan for failure and recovery.
• Work beside customer teams during rollout and improve the system until it becomes part of the workflow.
• Turn what works into reusable components, evaluation sets and playbooks for future Celeco deployments.

You will probably thrive here if

• You have at least one year of professional software or product engineering experience.
• You have shipped a real system used by other people and can explain what you owned, what broke and what you changed.
• You are strong in Python or TypeScript and comfortable moving across unfamiliar codebases, APIs, databases and cloud services.
• You have built with language or multimodal models and understand prompting, structured outputs, retrieval, tool use and model failure modes.
• You use Cursor, Codex, Claude Code or similar tools as part of your engineering workflow, while still reviewing, testing and understanding the code you ship.
• You can create an evaluation set, choose useful quality metrics and improve a system through error analysis instead of prompt guesswork.
• You can speak with an operator, an engineering team and a senior leader without losing the thread of the problem.
• You work well with incomplete requirements, write clearly and surface risks early.
• You care about whether people use what you build and whether it changes a business outcome.
• You can commit full-time and travel to customer sites when discovery or rollout is better done in person.

Experience with cloud deployment, containers, CI/CD, observability, enterprise integrations, authentication or security is useful. We do not expect one person to arrive knowing every framework, cloud or industry.

What you will get

• Direct ownership of live customer problems from discovery through production.
• Close collaboration with Celeco's founders and customer leadership teams.
• Exposure to different industries, operating models and technical environments.
• The freedom to choose the technical approach and the responsibility to prove that it works.
• A role in defining Celeco's engineering methods, reusable systems and technical culture while the company is early.
• A remote-first setup, with the option to work together in Bengaluru.

If the work sounds like you but your background is unconventional, apply. We care more about what you have built, how you think and how quickly you learn than pedigree.

Sapical  is looking for an experienced Full Stack Technical Lead to provide technical leadership, engineering governance, delivery management, and people leadership across multiple software development projects.

The role combines hands-on full-stack technical expertise with project delivery and team management responsibilities. You will be responsible for ensuring the successful delivery of scalable, secure, and high-quality enterprise applications.

The ideal candidate should have strong experience across React.js, Node.js, MongoDB, APIs, integrations, cloud technologies, and microservices, along with proven experience leading engineering teams.

Experience Required

• 8+ years of overall software engineering experience
• At least 3 years of experience in a Technical Lead, Engineering Lead, or Delivery Lead role
• Experience managing teams of 10+ members
• Strong experience in full-stack application development and technical leadership

Key Responsibilities

• Lead technical design, architecture reviews, and engineering governance across multiple projects.
• Provide technical oversight for React.js, Node.js, MongoDB, APIs, integrations, and cloud-based solutions.
• Manage multiple project streams, delivery plans, risks, dependencies, and resource allocation.
• Drive Agile delivery practices including sprint planning, estimation, tracking, and release management.
• Conduct code reviews and ensure adherence to engineering standards and best practices.
• Mentor development teams and support technical and professional growth.
• Collaborate closely with stakeholders, business users, architects, QA, and DevOps teams.
• Monitor project progress and provide regular status reporting to leadership.
• Support hiring, onboarding, performance management, and team development.
• Ensure successful delivery within agreed scope, schedule, quality, and budget expectations.

AI & Automation

• Drive the strategic adoption of AI and automation technologies across engineering teams.
• Identify opportunities to improve engineering productivity and delivery efficiency through AI and automation.
• Help reduce development effort and time-to-market through effective adoption of emerging technologies.

Technical Requirements

Frontend Technologies

• Strong hands-on experience with React.js
• JavaScript (ES6+) and TypeScript
• Modern JavaScript frameworks and state management libraries
• Experience building responsive and performance-optimized web applications

Backend Technologies

• Strong experience with Node.js
• Express.js and/or NestJS
• REST APIs and GraphQL
• Microservices architecture
• API integrations and enterprise application development

Databases

Experience with one or more of:

• MongoDB
• PostgreSQL
• MySQL
• MS-SQL

Cloud & DevOps

• Docker
• CI/CD pipelines
• AWS and/or Azure
• Monitoring and observability tools

Leadership & Delivery Competencies

• Project planning and delivery management
• Agile/Scrum methodologies
• Stakeholder management
• Risk and issue management
• Resource planning and team allocation
• Executive reporting and communication
• Team leadership and mentoring
• Continuous improvement and process governance

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related discipline
• Experience delivering enterprise-scale digital transformation projects
• Experience managing distributed teams
• Experience working in client-facing engagements

What Success Looks Like

• Successful delivery of multiple concurrent projects
• High customer and stakeholder satisfaction
• Strong engineering quality and governance
• Effective team leadership and retention
• Consistent adherence to project timelines and delivery commitments

Why This Role?

This is an opportunity to take ownership of full-stack engineering and technical delivery, while leading teams and driving engineering excellence across enterprise projects.

You will play a key role in shaping technical solutions, improving engineering processes, mentoring teams, and driving the adoption of AI and automation across engineering.

Key Skills

React.js | Node.js | TypeScript | JavaScript | Express.js | NestJS | MongoDB | PostgreSQL | REST API | GraphQL | Microservices | Docker | CI/CD | AWS | Azure | Agile | Technical Leadership | Team Management | AI & Automation

We're building in a market that hit $47B in 2026 and is on track to hit $107.5B by 2028 and we're not chasing that opportunity from the sidelines. Our founding team brings marketing expertise from Kotak and Amazon paired with deep AI chops, we were selected as one of just 20 startups by Google, and we already have paying customers like Kotak and Myntra using the product in production. Join us early and help build the infrastructure that turns AI marketing adoption (already at 88%) into real, scaled results for customers who are already paying for it, not case studies.

Founding Product Engineer, Applied AI

Location: Mumbai • Hybrid • Reports to: CTO

WHAT THIS ROLE ACTUALLY IS

Weve built a multi-agent AI system for marketing. It works well out of the box but every client (their data, workflows, brand rules, compliance constraints, output preferences) is different. Generic doesnt ship results. Customised does.

This role is the bridge: you sit between our agent architecture and the client’s reality. You understand both deeply, and you make the agents do what each specific client needs them to do.

Think Palantir Forward Deployed Engineer, but for AI agents. An engineer who owns product outcomes end-to-end.

WHAT YOU'LL DO

Day-to-day split: roughly 60% in Codex and Claude Code shipping customisations, 40% in client rooms understanding what to ship next.

• Customise the agents. Tune prompts, build new agent capabilities, configure workflows, wire up integrations. Codex and Claude Code are your primary IDEs. You ship working code, not specs for someone else to build.
• Own client outcomes end-to-end. From discovery to live deployment, you are the person responsible for whether the agents actually solve the client’s problem. No PM-engineer handoff to hide behind.
• Problem-solve in real time. Client says “the output tone is off for our brand” or “the research agent is missing X data source” — you diagnose, fix, and redeploy, usually within days.
• Hold your own on creative. When a CMO says “this doesn’t feel right,” you can question intelligently — is it the prompt, the input brief, the brand guidelines themselves, or the client’s own confusion? Most engineers reach for the prompt. The good ones diagnose first.
• Feed learnings back to core product. Anything that gets customised 3+ times becomes a platform feature. You decide what graduates.
• Build the playbook. As we scale from 10 to 50 to 100 clients, the customisation patterns you create become the foundation others work from.

WHAT YOU NEED

• Real engineering chops. You can read a codebase, write production code, debug agent failures, and ship to live clients. AI tools are your accelerant, not your crutch.
• Comfort with agents as a system. You understand how LLMs fail, why prompts drift, what context engineering means, when to use tools vs. fine-tuning, why eval harnesses matter. If “MCP,” “tool use,” and “agent harness” feel like jargon, this isn’t the role.
• Client-facing instincts. Comfortable in a room with a CMO, an enterprise IT head, and a junior brand manager — and you can switch register for each in the same meeting. If client calls feel like tax to you, don’t apply.
• Some creative literacy. You don’t need to be a designer. You do need to be able to tell the difference between “this output is technically broken” and “this output is technically fine but creatively wrong” — and chase the right thread.
• Bias toward shipping. A working hack today beats a clean design next quarter.

YOU'LL THRIVE HERE IF

• You’re an engineer who realised products live or die on customisation, not architecture.
• You’ve been frustrated by being kept away from customers.
• You like building with AI tools and want a role where that’s the job, not a side experiment.
• You like marketing as a domain — or you’re willing to fall in love with it.

YOU WON'T THRIVE HERE IF

• You want to optimise systems in a corner with headphones on.
• You think client calls are below your pay grade.
• You think AI is overhyped (we don’t).
• You need a fully scoped ticket queue and weekly sprint rituals.

Lead Product Engineer - Pod Captain 

A Little Bit About the Role

There is a version of this role that attracts the wrong person: a senior engineer who wants a title upgrade and a slightly bigger scope. That person will struggle here. The Lead PE is not a promotion for being a great individual engineer. It is a fundamentally different job.

Your success at this level is measured entirely by what your Island delivers — not by the quality of your own code. You will still write code, often the hardest and most risk-laden on the project: auth systems, payment integrations, data migrations, the things nobody else should touch. But that is a fraction of the role. The majority is managing delivery, owning the client relationship on the technical side, unblocking engineers before problems compound, and making scope calls under pressure with incomplete information.

You are also the technical and commercial bridge between your Island and the client. You own every piece of technical communication that goes to them — what is being built, what risks exist, what the honest timeline is. When a client pushes for something technically unsound, you push back directly and professionally, always with an alternative. When something breaks in production, you own the post-mortem process and the client receives it within 24 hours. You protect your team from unfiltered client pressure; you translate it into clear, actionable direction instead.

On top of delivery and client management, you are the AI operating standard for your Island. Every engineer on your pod uses Cursor and Claude within the rules you define. You set those rules before the first line of code is written, govern how they evolve, and you are accountable when AI-generated code ships without being understood.

If you are energised by all of that — by the accountability, by owning outcomes rather than tasks, by the combination of technical depth and people management — this role will suit you well. If you want to spend most of your time in code, this is not the right level.

AI Governance Expectation

You set the AI standard for your entire Island. If an engineer on your pod is shipping AI-generated code they do not understand, or underusing AI tools entirely, both are your problem to fix — not theirs alone.

At Lead level, AI governance means:

• Authoring the .cursorrules file before the first PR is opened. This defines how every engineer on the team writes code, uses Cursor, and structures prompts. You update it as the team learns, and you submit it to the Fountane Mainland at the close of every engagement.
• Evaluating new AI tools before they reach client code. You are the gate. A tool that looks useful in a demo can create untraceable technical debt in production. You decide what enters the workflow.
• Governing prompt discipline across the team: scoped prompts, codebase context hygiene, no AI-generated code that the author cannot explain line by line.
• Using Claude for architecture reasoning, sprint planning, risk documentation, and client-facing technical communication — not just Cursor for code generation. AI works at every layer of the Lead role, not just the coding layer.
• Staying ahead of the Golden Stack. You should know what Cursor and Claude can and cannot do at the codebase level better than anyone on your Island. When the Mainland updates the standard toolchain, you integrate the change into your Island’s workflow first.

Key Responsibilities

Technical Architecture & Standards Ownership

Design the full-stack architecture for every engagement before the first sprint starts: service boundaries, API contracts, database schema, state management strategy across web and mobile surfaces, and the security baseline. Author the .cursorrules file that governs how the entire Island writes code and uses AI. Own the highest-risk code personally — auth systems, payment integrations, live data migrations — these are not delegated regardless of workload. Enforce Mainland security standards across the entire codebase: input validation, correct auth scoping, safe data handling. If a security issue reaches production that was visible in a PR, that is a failure you own.

CE Prototype Gatekeeping

Review every Concept Engineer prototype before any engineer touches it. This is not a courtesy review — you have veto authority. If the scope is technically unrealistic for the sprint, the architecture is unbuildable as specified, or the prototype makes promises the codebase cannot keep, the sprint does not start until those are resolved. The time to surface a structural problem is before it is built, not after it is demoed. Produce a written checklist verdict for every prototype review — approved, approved with conditions, or blocked with reasons.

Client Technical Communication & Scope Ownership

Own all technical communication with the client directly. This means: what is being built each sprint, what risks exist and what is being done about them, honest timelines when estimates change, and clear explanations of technical decisions in plain language. Push back on risky or scope-expanding requests professionally and always with an alternative — “we cannot do X because Y; here is what achieves the same outcome.” Manage scope creep actively: every request that expands the engagement goes through you, gets assessed for impact, and is either absorbed, priced, or declined with a rationale. Renewal conversations are yours to lead in coordination with the CE.

Island Integration Audit

When a prospective client wants fractional augmentation — one or two roles rather than a full Island — you conduct the Island Integration Audit. This means evaluating their existing engineering team against Fountane Mainland SOPs: coding standards, AI tool usage, deployment practices, and documentation quality. If they pass, fractional deployment proceeds. If they do not, you produce a written audit report that either recommends full Island deployment or a Mainland upskilling programme. You are protecting your team’s velocity — a fractional deployment into a dysfunctional team destroys it.

Delivery & Velocity Management

Review the work cycle board every morning. Flag anything stuck, stale, or at risk before it becomes a client problem — not after. Communicate risks to the CE proactively with options, not just problems. Track every engineer’s billing hours: a shortfall spotted on Wednesday is a Thursday conversation, not a Friday surprise. If an engineer is consistently under-billing, that is either a workload problem, a capability problem, or a motivation problem — each has a different resolution and you are responsible for diagnosing which one it is.

Production Incident Ownership

When something breaks in production, you own the resolution process end to end: take technical lead, make the call on rollback vs. hotfix, communicate status to the client directly if the incident affects them, and own the post-mortem. The client receives the post-mortem within 24 hours of resolution — this is a hard commitment, not a target. The post-mortem covers: what happened, why it happened, what was done to fix it, and what structural change prevents recurrence. You produce it; it is not delegated to the engineer who caused the issue.

Automation & Infrastructure Boundary Arbitration

The Automation Engineer owns the test gates within the CI/CD pipeline. The Infrastructure Engineer owns the pipeline configuration itself. When these overlap and conflict — which they will — you arbitrate. The resolution must be documented in the Island’s .cursorrules and SOP onboarding document so the boundary does not need to be relitigated every sprint. This is not optional housekeeping; an unresolved boundary between these two roles is one of the most common sources of deployment failures on Islands.

Full Stack Ownership — Web & Mobile

You review and own work across the entire application layer: React / Next.js web frontends, React Native or Flutter mobile apps, Node.js / Python backends, and database schema. You cannot delegate a review of mobile code because you do not know mobile, or backend code because your background is frontend. If there is a gap in your full-stack depth, that is something to resolve before taking this role, not on the job.

People Management & Mentoring

Hold bi-weekly 1:1s with every engineer on the Island — focused on growth, blockers, and career direction, not status updates. Status belongs on the board; 1:1s are for the person. Address performance gaps early, directly, and specifically: a pattern spotted in week two is a conversation in week two, not month three. Protect the team from unfiltered client anxiety — absorb it, process it, and give the team clear direction instead of noise. If an engineer is struggling, that is your problem to solve before it becomes the client’s problem to notice.

Network Contribution

At the close of every engagement, submit to the Fountane Mainland: the .cursorrules file, all prompt templates used, a short retrospective on what worked and what did not, and any reusable patterns or scripts developed during the engagement. This is a Lead-level obligation, not a nice-to-have. The network’s collective capability grows through what Leads bring back from the field. An engagement that ends without a Mainland submission has left the network no smarter than it was before.

Qualifications

• 8+ years of software engineering experience, with at least two years in a role where you were accountable for delivery outcomes — not just your own code. You should be able to describe an engagement where something went wrong on your watch, what you did about it, and what you would do differently. If your experience is entirely individual-contributor, this role will be a difficult fit.
• Genuinely full stack across web and mobile: React / Next.js, React Native or Flutter, Node.js or Python, and database architecture including schema design and migrations. You review and own work across all of these surfaces — not just the ones you are most comfortable in.
• Hands-on, daily Cursor and Claude usage with the ability to set and enforce standards for how a team uses them — not just personal proficiency. You should be able to describe the .cursorrules file you would write for a standard SMB engagement and explain the decisions behind it.
• Proven ability to communicate technical risk and decisions directly to non-technical clients — not through a PM, directly, in plain language. You should be able to describe a client pushback you navigated and how you handled it.
• Experience managing scope on a real engagement: a client who wanted more than was in the contract, and how you resolved it without damaging the relationship or the team’s velocity.
• Has conducted security-aware architecture design: auth systems, input validation, safe data handling. You should be able to describe a security decision you made and why.
• Has led or coordinated a small engineering team — run 1:1s, addressed performance gaps, made scope calls under pressure. Management experience at a staffing agency or outsourcing firm counts if the accountability was real.
• Comfortable having direct, specific performance conversations early — not after the situation has compounded. You should be able to describe a time you addressed a performance issue at the first sign rather than waiting.
• Bachelor’s or Master’s in Computer Science or a related field, or equivalent experience.

About Fountane

Fountane is a technology ventures lab - one part product studio, one part startup engine. We build high-quality software and AI products for clients ranging from fast-moving startups to large enterprises, and we co-build and invest in new companies when we see the right opportunity.

Founded in 2017 and headquartered in Minneapolis, we have grown to 60+ people across four continents and were recognised as one of America’s fastest-growing companies, ranking No. 699 on the Inc. 5000 with 595% three-year growth.

We are serious about craft, direct about expectations, and operate at the frontier of AI-assisted engineering. Lead PEs here carry real authority and real accountability — over delivery, over people, and over client outcomes. If that combination is what you are looking for, this is the place.

Sr .NET Lead

Position:– Dotnet Developer (.NET 8+)

Experience: 8+ Years

We’re looking for a strong .NET 8+ Developer with a passion for building modern, scalable web apps using the latest tools and practices. If you're comfortable with microservices, observability (OpenTelemetry), NoSQL (MongoDB), and modern frontends like React, we want to hear from you.

Sr. Dot Net Engineer

We are looking for a Senior .NET Developer with deep expertise in distributed systems, event-driven architecture, and cloud-native development. This role requires someone who can own features end-to-end — from database schema to API contract to event flow to deployment — while leveraging AI-assisted development tools for rapid, high-quality delivery.

Required Skills & Experience

●  Mandatory: Hands-on .NET development experience combined with daily AI-assisted development — this is a non-negotiable requirement for this role

●  

Core .NET Expertise (5+ years) - C# 12+ and .NET 8/9, ASP.Net Core, Entity Framework Core, Dependency Injection, Design Patterns (including Saga Pattern and Decorator Pattern), SOLID principles

●  Distributed Systems & Messaging: Message brokers, MassTransit, Event driven architecture

●  Cloud & Infrastructure: AWS, Docker & Kubernetes

●  Databases: SQL Server, MongoDB, Redis

●  Security & Compliance: Authentication, Identity Providers, Multi-tenant isolation

●  AI-Assisted Development: Daily use of AI coding assistants, Critical evaluation of AI output, AI-assisted code review, AI-assisted documentation, AI-assisted debugging

●  What We Don't Want: Engineers who blindly accept AI output without reading and understanding the code

Nice to Have: Financial services domain knowledge — Payments, remittances, FX, settlements, ACH/SWIFT, card processing, KYC/AML compliance

Key Requirements / Skills

• 6+ years of overall experience in software development with strong expertise in building scalable web applications.
• 2+ years of experience as a Technical Lead, managing development teams and driving project delivery.
• Strong technical decision-making ability, including architecture design, technology selection, and implementation of best practices.
• Front-end expertise: Strong experience in React, JavaScript, TypeScript, and building responsive and user-friendly UI/UX.
• Back-end development: Hands-on experience with Node.js, RESTful APIs, API design, and server-side architecture.
• Gen AI Expertise: Experience in building RAG & LLM Systems, implementing AI/ML models or integrating AI-based solutions to solve business problems.
• Cloud & DevOps exposure: Experience with AWS/Azure, understanding of CI/CD pipelines, and cloud-based deployments.
• Code quality & best practices: Experience in code reviews, Git version control, and ensuring maintainable and secure code.
• Team leadership: Ability to mentor developers, guide technical discussions, and collaborate across teams.
• Strong communication skills to effectively interact with technical and non-technical stakeholders.
• Experience working in high-compliance environments such as healthcare systems is a plus.

Education Qualifications:

• B.Tech/M.Tech in CSE/IT/AI/ML from a good university

Senior Agentic Engineer — Ai1 Platform (Operations)

Team: Operations · Type: Full-time · Location: Fully remote (global, async-first)

Who we are

MyZone AI builds and runs Ai1 — a managed, multi-agent AI platform that gives each client their own isolated, always-on team of AI agents working across the channels and tools they already use. We're a small, AI-first, high-trust team that ships like a much bigger one. We work fully remote and async — what you ship and how clearly you write matter more than your hours.

The role

You'll join the Operations team. 

• Agentic engineering — complex agent skills and workflows, multi-agent orchestration, custom integrations, and the prompting and guardrails that make autonomous agents reliable.

What you'll do

Build agents that do real work

• Design complex, reusable skills and multi-step recipes that automate entire business processes — production automations, not demos.
• Architect multi-agent workflows: delegation, parallel execution, and agents that hand off and reassemble work.
• Build custom MCP connectors and API integrations for any tool that doesn't have one yet.
• Engineer robust prompts, human-in-the-loop controls, and built-in QA so automations are safe to run autonomously.
• Ship automations as self-contained installers that deploy across many client instances with zero rework.

Own application code end-to-end

• Own one or more services in our modular platform (Node/Express backends, React frontends) — schema, API, and UI.
• Ship features across CRM, operations, pipeline, reporting, onboarding, assessments, and chatbots.
• Contribute to our Next.js portal (Next.js 15, TypeScript, Prisma, PostgreSQL).
• Keep your components healthy: clean migrations, green CI, solid tests.

Set the bar

• Work clean: feature branches, real PRs, green CI, small changes, semantic versioning.
• Be security-conscious by default — credentials are treated like credit-card numbers; high-risk actions route through human review.
• Mentor, set patterns, and raise the team's technical level.

Who we're looking for

Must-haves

• 5+ years of professional software engineering with strong full-stack depth: Node.js / TypeScript and modern React.
• Hands-on experience building AI agents in production — tool/function calling, orchestration, memory, and evaluation. You've shipped something that uses an LLM to reliably do real work.
• Fluency with the Anthropic / Claude API (or equivalent) and real depth in prompt/context engineering.
• Strong with PostgreSQL and pragmatic API design.
• Able to own a service end-to-end and ship independently in a low-oversight, async environment.
• Excellent written communication and sound judgment around security and autonomous actions.

Bonus

• Built MCP connectors, agent frameworks, or similar orchestration layers.
• Next.js 15, Prisma, Vercel, monorepos (pnpm / Turborepo).
• Light DevOps: Linux VPS, PM2, nginx, CI.
• Used coding agents (Claude Code–style tools) to build real things.
• Integrations: Slack/Teams apps, Twilio, Google Workspace, GitHub.

How we work

Fully remote, global, async-first — no required location. Small, high-trust, and low-bureaucracy, so you'll own real work and thrive without hand-holding. Everyone here builds automations, versions their work, and maintains what they ship.

MyZone AI is an equal-opportunity employer. We hire the best person for the work, wherever they are.