Senior Full-Stack + Agentic AI Engineer

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.

We are building an advanced, AI-driven multi-agent software system designed to revolutionize task automation and code generation. This is a futuristic AI platform capable of:

✅ Real-time self-coding based on tasks  

✅ Autonomous multi-agent collaboration  

✅ AI-powered decision-making  

✅ Cross-platform compatibility (Desktop, Web, Mobile)  

We are hiring a highly skilled **AI Engineer & Full-Stack Developer** based in India, with a strong background in AI/ML, multi-agent architecture, and scalable, production-grade software development.

### Responsibilities:

- Build and maintain a multi-agent AI system (AutoGPT, BabyAGI, MetaGPT concepts)  

- Integrate large language models (GPT-4o, Claude, open-source LLMs)  

- Develop full-stack components (Backend: Python, FastAPI/Flask, Frontend: React/Next.js)  

- Work on real-time task execution pipelines  

- Build cross-platform apps using Electron or Flutter  

- Implement Redis, Vector databases, scalable APIs  

- Guide the architecture of autonomous, self-coding AI systems  

### Must-Have Skills:

- Python (advanced, AI applications)  

- AI/ML experience, including multi-agent orchestration  

- LLM integration knowledge  

- Full-stack development: React or Next.js  

- Redis, Vector Databases (e.g., Pinecone, FAISS)  

- Real-time applications (websockets, event-driven)  

- Cloud deployment (AWS, GCP)  

### Good to Have:

- Experience with code-generation AI models (Codex, GPT-4o coding abilities)  

- Microservices and secure system design  

- Knowledge of AI for workflow automation and productivity tools  

Join us to work on cutting-edge AI technology that builds the future of autonomous software.

Responsibilities Include:

● Architecting, building, testing, and deploying applications that support our transportation network

● Modifying designs and specifications of complex applications

● Collaborating and adding value through participation in peer code reviews, providing comments and suggestions

● Leverage AWS and other cloud technologies to design and implement systems in a serverless and event-driven environment

● Working with technical and non-technical end-users, other engineers, and product managers in a cross-functional, quick-moving, and collaborative environment

● Analyzing code, requirements, system risks, and software reliability and providing recommendations on how to leverage our technology more efficiently

● Working with Product and Design to confirm requirements, prioritization, and development of new features

● Design and implement LLM-powered features to solve complex logistics challenges, automate manual operational workflows, and unlock new efficiencies for our network.

● Champion AI-assisted engineering practices by integrating machine learning and intelligent automation into our CI/CD pipelines to predict deployment risks and accelerate delivery cycles.

What You Bring:

● Ability to adapt to changing requirements and work in a fast-paced environment.

● Ability to work effectively in a cross-functional team environment.

● 7+ years of experience building, testing and deploying applications in high-traffic production environments

● 7+ years of experience developing software with Javascript, Node.js and React

● Enjoys taking initiative, is a self-starter, willing to move fast and ship quick, and is excited about collaborating on big challenges

Preferred Qualifications:

● Experience in transportation, logistics or network orchestration systems is highly desirable

● Experience working in a remote first environment.

● Proficiency with AWS, GCP, or similar cloud platforms.

● Strong skills in React and Node.js for end-to-end development. 

About us

MyRico builds personal AI agents for enterprise, the copilots and digital employees that make humans more productive. The MyRico agents sit at the intersection of enterprise memory, high-end security, and an ever-expanding set of capabilities. We're a small team shipping fast, and the product is live with real customers today.

The role

Full-time · Bangalore

You'll own the systems that make an autonomous agent trustworthy in production. This is not just prompt engineering, and it's not model training - it's that and all the engineering layers in between: model steering, memory architecture, orchestration design, latency optimization, deterministic vs non-deterministic systems tradeoff, deployment, and operator tooling.

Concretely, the kind of work you'd have done here last week would include enhancing agent memory systems, runtime and scheduling reliability and predictability, adding new capability and tools to deployed agents, operator tools, live system debugging and benchmarking various models for price, latency and quality. And that is just last week. We are a small nimble startup rapidly working to address customer needs in this growing space, so things change rapidly.

What we're looking for

• More than 7 years of software engineering, with real production ownership of distributed or stateful systems - you've been paged for something you built and made it not happen again.
• Strong understanding of LLM based native app building, combining classic and model driven applications to get the best of both. You've built on LLMs beyond demos: agent frameworks, tool use, context management, eval fixtures, and you know why "it worked in the transcript" isn't evidence.
• Python and shell in production settings; comfortable in TypeScript/Node. You write boring, testable code and prefer the standard library to a new dependency.
• Systems taste: append-only logs, idempotent reconciliation, fold-the-events state machines, and read-only debugging surfaces feel like home.
• Evidence discipline: tests before features, claims backed by quoted observations, decisions written down.

Nice to have

• Experience running the combination of multi-tenant and single-tenant / on-prem-style fleets with ability to handle per-customer isolation, upgrade paths, migration compatibility in both setups.
• Security instincts for products that touch highly sensitive data and systems, including things like executives' email, calendars, and messages: least privilege, loopback-only services, secrets that never hit a log.
• You already orchestrate AI coding agents in your own workflow and have opinions about where they break.

How we work

Small team, high trust, written decisions. Designs get adversarial review before code; PRs get automated review driven to zero open findings; features aren't done until verified on a live system. AI agents do a large share of the implementation, your leverage is judgment: framing the problem, freezing the right design, and knowing when the machine is wrong.

Full-Stack Software Engineer | Remote

We're hiring a product-focused Full-Stack Engineer to join a small, fast-moving tech team. This is a hands-on role you'll build complete features across frontend, backend, APIs, databases, deployment, and increasingly, AI-assisted workflows.

What You'll Do:

• Build and ship full-stack features using modern JS/TypeScript, plus Java or Node.js on the backend
• Work across frontend, backend, APIs, databases, integrations, and deployment
• Apply secure engineering practices (auth, input validation, secrets, dependencies)
• Use AI tools for coding, debugging, testing, and code review
• Explore AI agents, tool calling, and MCP-based integrations

What We Need:

• 3+ years of professional software engineering experience
• Strong JS/TypeScript skills; experience with Angular or React
• Backend experience with Java, Node.js, or similar
• Comfortable with REST APIs, databases, Git, cloud environments
• Awareness of OWASP principles and application security
• Interest/experience in AI dev tools, Docker, CI/CD

Role & Responsibilities

• Own end-to-end architecture, system design, development, and production deployment of scalable, AI-powered applications.
• Architect and develop high-performance backend services using Node.js, NestJS, TypeScript, Express.js, and Go.
• Design scalable web applications using React.js and Next.js, and cross-platform mobile applications using Flutter and Dart.
• Design distributed systems, microservices, event-driven architectures, and real-time applications capable of handling massive data volumes and high concurrent traffic.
• Design and optimize PostgreSQL/MySQL databases, MongoDB, Redis caching, database indexing, transactions, and query performance.
• Build real-time ride-booking, driver-allocation, location-tracking, and proximity-based matching systems using geospatial technologies such as PostGIS.
• Design and implement REST APIs, WebSockets, secure authentication, authorization, RBAC, and third-party integrations.
• Build and integrate Generative AI applications, LLM-powered chatbots, AI agents, RAG pipelines, embeddings, vector databases, tool calling, and intelligent automation workflows.
• Develop AI and backend services using Python and integrate LLM platforms such as OpenAI, Claude, and Gemini.
• Architect secure payment integrations, transaction workflows, webhook processing, idempotency, and payment reconciliation.
• Design and implement cloud-native infrastructure using AWS, Docker, CI/CD pipelines, and production monitoring tools.
• Ensure application security, scalability, reliability, performance, maintainability, and cost efficiency.
• Lead technical decision-making, code reviews, debugging, performance optimization, documentation, and mentoring of developers.
• Independently own critical engineering deliverables and drive products from concept and architecture through development, testing, deployment, and production support.

Preferred Candidate Profile

• 710+ years of software development experience, with substantial hands-on experience in technical architecture and production-grade application development.
• Expert-level proficiency in Node.js, NestJS, TypeScript, REST APIs, backend architecture, and microservices.
• Strong experience with React.js, Next.js, and modern frontend architecture.
• Hands-on experience with Flutter and Dart for Android and iOS application development.
• Proven experience designing scalable systems, handling large data volumes, concurrent workloads, and performance-critical applications.
• Strong experience with PostgreSQL, database design, indexing, query optimization, transactions, Redis, and geospatial systems.
• Practical experience building and deploying LLM-powered applications, AI agents, RAG systems, embeddings, vector search, and AI workflow automation.
• Proficiency in Python for AI integrations and backend services; Go language experience is highly desirable.
• Strong understanding of authentication, authorization, application security, payment integrations, and secure API design.
• Hands-on experience with AWS, Docker, CI/CD, Git, production deployments, logging, and monitoring.
• Familiarity with Kafka/RabbitMQ, Kubernetes, LangChain/LlamaIndex, and event-driven architectures is an advantage.
• Exceptional system-design, analytical, debugging, and problem-solving skills.
• Strong ownership, independent execution, technical leadership, communication, and mentoring abilities.
• Experience in startups or building products from scratch is highly desirable.

What We Expect

We are looking for a highly hands-on technical leader who can independently architect, design, develop, optimize, and deploy complex production systems. The ideal candidate must demonstrate genuine technical depth, strong engineering judgment, and the ability to lead end-to-end product development across backend, web, mobile, cloud, and AI technologies.

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

  We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

  We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

  We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

  We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Experience Level

This role is ideal for engineers with total 3+ years of experience with a proven track record of shipping complex projects successfully.

An experienced individual contributor and leader who thrives in large, complex projects with widespread impact.

What You’ll Do as a Software Craftsperson 

• Design and build high-quality, maintainable systems using disciplined engineering practices such as TDD, continuous refactoring, and pair programming 
• Operate in an AI-native development model, using AI as a collaborator to explore architecture and design, accelerate development, and continuously improve systems while applying strong judgment to ensure that speed never compromises quality 
• Take end-to-end ownership of outcomes from problem understanding and system design to implementation, deployment, and operation in production 
• Make thoughtful design decisions that balance simplicity, scalability, and long-term maintainability in real-world systems 
• Maintain a high bar for engineering quality through rigorous testing, code reviews, and continuous feedback 
• Investigate and resolve production issues, and implement systemic improvements to prevent recurrence 
• Work directly with clients, navigate ambiguity, and translate business problems into well-designed technical solutions 
• Contribute to improving team practices, tooling, and systems to raise the overall quality and effectiveness of engineering 

Requirements

What You’ll Bring 

• 3+ years of experience building high-quality, production systems (flexible based on demonstrated capability) 
• Strong fundamentals in software engineering, including object-oriented design, system design, and testing practices such as TDD 
• Demonstrated ability to build simple, maintainable, and scalable systems with a focus on long-term reliability 
• Proficiency in one or more modern technologies, Python, PHP, JavaScript, or TypeScript, with the ability to learn new technologies quickly 
• Deep experience working with Git in collaborative environments, including managing shared codebases, conducting code reviews, and maintaining a high bar for quality 
• Ability to operate effectively in an AI-native workflow using AI as a collaborator to explore solutions and accelerate development, while applying strong judgment to ensure correctness, quality, and maintainability 
• Clear thinking and strong problem-solving ability, with the capacity to break down complex problems into simple, well-structured solutions 
• A strong sense of ownership — you take responsibility for outcomes, care deeply about quality, and are not comfortable shipping work that does not meet your standards.

Benefits

Life at Incubyte 

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered. 

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion. 

Perks

• Dedicated learning & development budget. 
• Sponsorship for conference talks. 
• Comprehensive medical & term insurance. 
• Employee-friendly leave policies. 
• Home Office fund 
• Medical Insurance

Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World's Best Employers 2025) is consistently listed among the most admired companies in the world. 

This role is part of Cognizant IOA (Intuitive Operations and Automation) — and more specifically, a product team with its own origin story. We started as Matterway, a German startup building automation software from scratch. We were acquired by Cognizant, but we kept our team, our culture, our pace, and our way of working. We move like a startup, think like a startup, and now do it with the backing of a global company. 

We combine human expertise with intelligent automation, ML operations, and digital experience solutions to help technology and digital-native companies build smarter, more adaptive operating models. 

What's the opportunity? 

We are looking for Senior Product Engineers to join our team. We're a tight crew of 5 senior engineers, from different corners of the world. We're hiring 3 more people, and those people will shape what this team becomes. 

We're building a platform to support the agentification of our operations. You'll work across a suite of products including a cloud platform for process optimization, desktop application, browser extension, and specialized AI agents. 

This is genuinely frontier work: we don't follow AI trends, we implement them. New model drops on a Monday; we've prototyped with it by Wednesday. 

We believe this is the most exciting time to join. Be part of the founding R&D talent in this area and help set the technical bar for everything that comes next. 

What will you be doing? 

Your day-to-day responsibilities: 

• Design and evolve the core architecture of our platform 
• Set technical standards and take ownership of complex projects end-to-end 
• Work on a well-architected, fast-evolving TypeScript codebase using technologies such as React, Node.js, Electron, and GraphQL 
• Collaborate with product managers, designers, and engineers to solve challenging technical and business problems, with real autonomy 
• Participate in the full development lifecycle: scoping, design, estimation, coding, testing, debugging, code reviews, maintenance, and support 
• Evaluate and implement proofs of concept using the latest AI tools and models 

You will know you're successful if: 

• You develop projects independently until they deliver their intended business value 
• You keep top-notch software quality standards about design, implementation, and documentation 
• You're the person who brings something new to the team's radar, a model, a technique, a tool, before anyone else has heard of it 

What makes you a great fit 

Must-haves: 

• Excellent English (C1+) with exceptional written and verbal communication 
• Strong proficiency with TypeScript across frontend and backend, including building and maintaining Node.js-based services 
• Experience in frontend development using modern frameworks such as Vue.js or React 
• Knowledge of any E2E testing framework such as Playwright, Puppeteer, Selenium, Cypress 
• Ability to work independently and take ownership of deliverables 
• Strong technical fundamentals, genuine intellectual curiosity, and a drive to keep getting better 
• You follow AI closely, not just as a user but as someone who reads the papers, watches the releases, and has opinions. You're excited about where this is going and want to be building at the edge of it 

Nice-to-haves: 

• Familiarity with AI-coding tooling (Claude Code, Cursor, OpenCode, etc.) 
• Experience with cloud infrastructure (AWS, Azure or GCP) and infra-as-code deployment 
• Having built or maintained CI/CD pipelines or workflows, especially GitHub actions 

Why join us? 

• Be at the cutting edge of AI agents and applying LLMs to real-world use cases, not in theory but in production 
• Work on hard problems with high agency: your ideas get heard; your decisions get shipped 
• Join a small but growing internationally distributed team. 
• giving you real influence over how it evolves 
• The resources of a global company with the speed and culture of a startup 
• Remote-first set-up, with the option to work from one of our 13 locations in India: Chennai, Bangalore, Hyderabad, Pune, Mumbai, Gurgaon, Noida, Kolkata, Kochi, Coimbatore, Bhubaneswar, Mangalore, and Indore 
• Flexible working hours 
• Collaborative, pragmatic engineering culture focused on outcomes 
• Fast-growing team within Cognizant, with access to global resources and real career opportunities 

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.

Senior AI Engineer

Code Generation, Agent Architecture & LLM Systems

📍 Mumbai (On-site) | Full-time | 5+ years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior AI Engineer for a dedicated client engagement focused on building an AI-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code.

The mandatory requirement for this role is hands-on production experience shipping LLM-powered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage.

The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy.

You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.

Responsibilities:

Agent Architecture

Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions.

Make and revisit architectural decisions on single-agent vs. multi-agent designs, including planner/executor splits and dedicated build-repair sub-agents.

Code Generation Pipeline

Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit.

Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies.

Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.

Self-Repair Loop

Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation.

This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.

Context Management

Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval.

Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes.

Own token budgeting and prompt caching strategy.

Prompt Engineering as a Discipline

Own the system prompt and per-task prompt variants (new feature, bug fix, styling change).

Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites.

Version prompts like code with changelogs and rollback capability.

Evaluation and Quality Measurement

Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant.

Define regression gates that block quality-degrading changes from shipping.

Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time.

This responsibility is non-negotiable at this level.

Model Strategy and Cost

Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation.

Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection.

Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.

Safety and Reliability of Agent Behaviour

Defend against prompt injection from user content and fetched web content.

Ensure secrets never appear in generated client code.

Define what the agent's tools may and may not do in collaboration with the platform team.

Contribute to output moderation and abuse-pattern awareness.

Mentorship and Engineering Standards

Run code reviews, define engineering conventions for AI work, and raise the engineering bar across the AI team.

Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.

Requirements:

Hands-on Production Ownership of LLM-Powered Systems with Agent Architectures (Mandatory)

Must have personally shipped and operated at least one complex production AI system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost.

POCs, internal demos, and tutorial-grade work do not qualify.

5+ Years of Professional Software or AI Engineering Experience

With at least 3 years focused on LLM applications, AI engineering, or production AI systems.

Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.

Strong Python Proficiency and Service Development

Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging.

Not notebook-only.

Depth Across LLM APIs and Agent Systems

Production experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together).

Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.

Hands-on with tool calling, structured outputs, and multi-step reasoning.

Demonstrated, Systematic Evaluation Practice - Non-Negotiable

Must have built evaluation harnesses that gate production releases, not ad-hoc testing.

Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval.

Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.

Cost Discipline for Production AI

Track record of measurable cost optimisation on production AI features.

Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.

AWS Working Knowledge

Hands-on with EC2, S3, IAM, and Docker.

Comfort with CI/CD workflows and deploying AI services.

Awareness of LLM Security Failure Modes

Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.

Nice to Have

• Experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work
• MCP server authoring
• Open-source AI contributions
• Published technical writing on LLM systems
• Multi-modal model experience
• Fine-tuning exposure (LoRA, QLoRA, PEFT)