AI Engineer - Full Stack Developer

Position: Senior/Lead Full Stack Engineer – Gen AI / Agentic AI

Experience: 7+ Years

Employment: Permanent Position

Location: Banglore / Hyderabad

Job Summary

We are looking for a Senior/Lead Full Stack Engineer – Gen AI / Agentic AI with strong hands-on experience in Python, React.js, MongoDB, Java/Spring Boot and Generative AI/Agentic AI.

The candidate should have experience designing and developing scalable enterprise applications and implementing production-grade LLM, RAG, AI Agent and multi-agent solutions.

Key Responsibilities

• Design, develop and maintain scalable full-stack applications using Python, React.js, MongoDB and Java/Spring Boot.
• Build production-grade Generative AI and Agentic AI applications using LLMs and modern AI frameworks.
• Develop RAG pipelines, AI agents, tool calling, memory management, planning and agent orchestration.
• Work with LangChain, LangGraph, MCP, vector databases and semantic search.
• Develop Python-based APIs, microservices and asynchronous applications using FastAPI/Flask/Django.
• Build REST APIs and event-driven microservices with focus on scalability, performance and resilience.
• Integrate LLMs, embeddings, vector stores and external enterprise tools/services.
• Implement prompt engineering, LLM evaluation, guardrails and AI observability.
• Develop responsive front-end applications using React.js.
• Work with MongoDB, SQL and hybrid data models.
• Implement CI/CD pipelines and support cloud/OCP deployments.
• Follow secure coding, testing, code quality and performance best practices.
• Participate in architecture, technical design, code reviews and mentoring of team members.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.

Mandatory Skills

1. Python
2. React.js
3. Gen AI / Agentic AI
4. RAG + LLM
5. LangChain / LangGraph
6. MongoDB
7. Java + Spring Boot
8. REST APIs / Microservices
9. Vector Databases / Embeddings
10. MCP / AI Agent orchestration

Good to Have

• FastAPI / Flask / Django
• Kafka / Solace
• Docker / Kubernetes
• AWS / Azure / GCP / OCP
• CI/CD – Jenkins / GitHub Actions
• LLMOps / AI evaluation / observability
• ELK / Grafana / Splunk / AppDynamics
• SQL / NoSQL
• Agile/Scrum

Role: Full Stack GEN AI Engineer

Location: Remote - Bengaluru

Duration: Fulltime With VDart Digital

The role demands a developer who is not just familiar with Large Language Models (LLMs), but is an expert in building autonomous agentic workflows using the modern GenAI stack (LangChain, CrewAI, Vector DBs). Expertise in system design, cloud-native technologies, and CI/CD for AI-driven applications is essential for this high-impact delivery role.

Responsibilities

· Design, develop, and maintain full-stack applications that are scalable, robust, and meet the company's quality standards, with a specific focus on Generative AI integration.

· Agentic Orchestration: Build and deploy sophisticated multi-agent systems and autonomous workflows using frameworks like LangChain, CrewAI, or LangGraph.

· Collaborate effectively with cross-functional teams to define, design, and ship new features that bridge the gap between raw AI power and intuitive user workflows.

· Exhibit strong problem-solving skills with an emphasis on product development and driving architecture choices that enable a world-class user experience.

· Utilize a variety of modern web technologies and frameworks (React.js, Angular, or Vue.js) to build responsive and accessible user interfaces.

· Develop and maintain RESTful APIs and services with optimal performance and scalability, handling streaming AI responses and complex function-calling logic.

· Ensure code quality, organization, and automatization through best practices, including unit tests for prompts, model evaluation pipelines, and automated CI/CD for AI-driven features.

· Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using Vector Databases and advanced retrieval techniques.

· Adapt to emerging technologies and frameworks, specifically new GenAI tools and frontier models, and apply them to operational and business needs.

· Manage individual project priorities, deadlines, and deliverables with minimal supervision.

Skill Requirements

· Excellent oral and written communication skills, with the ability to articulate complex AI and technical ideas to both technical and non-technical audiences.

· Profound knowledge of application development, data structures, networking, operating systems, and DBMS.

· Strong proficiency in backend programming languages for API development such as Python, Java, JavaScript (Node.js), or Go.

· Expertise in front-end technologies and frameworks such as React.js, Angular, or Vue.js.

· GenAI & Agentic Tools: Deep hands-on experience with LangChain, CrewAI, or AutoGen. Ability to manage agent memory, state, and tool-calling.

· In-depth understanding of SQL/NoSQL databases, data modeling, and experience with Vector Databases for RAG implementations.

· Solid grasp of system design, microservices architecture, and cloud-native technologies including Docker, Kubernetes, and GitHub Actions.

· Experience with distributed computing, machine learning frameworks, and tools, with a primary focus on Generative AI.

· Desirable (Good to Have): Experience with Generative or Adaptive UI development, where the interface dynamically adapts or renders components based on LLM outputs and real-time AI reasoning.

· A strong desire to learn and master new technologies and techniques in the rapidly evolving GenAI landscape.

Qualifications

· Bachelor’s degree in Computer Science, Engineering, or a related field.

· A minimum of 3-5 years of experience in full-stack development, with a proven track record of building and deploying Generative AI applications and agents.

· Portfolio of successfully deployed web applications and services, specifically showcasing AI agents, RAG implementations, or complex AI-driven features.

Key Skills :

• Builds AI-powered business applications end to end, from the Python/FastAPI service layer through

to React-based user interfaces, deployed on Databricks

• Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including

decision capture, audit logging and file exports for downstream systems

• Codes rule-based decision engines in Python (e.g. allocation or replenishment logic) that work

alongside ML models

• Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited

outputs

• Writes performant SQL against governed data and ensures services operate within defined access

boundaries

• Builds interactive screens, dashboards and conversational interfaces that let users review and act

on AI recommendations

• Works closely with GenAI/ML engineers, data engineers and BA

Only immediate joiners are considered.

Note: Only Immediate joiners are considered

Key Skills:

• Builds AI-powered business applications end to end, from the Python/FastAPI service layer through to React-based user interfaces, deployed on Databricks
• Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including decision capture, audit logging and file exports for downstream systems
• Codes rule-based decision engines in Python (e.g. allocation or replenishment logic) that work alongside ML models
• Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited outputs
• Writes performant SQL against governed data and ensures services operate within defined access boundaries
• Builds interactive screens, dashboards and conversational interfaces that let users review and act on AI recommendations
• Works closely with GenAI/ML engineers, data engineers and BA

Primary tech stack:

Python, Fast API, REST API design, SQL, Databricks Apps, Databricks SQL, Unity Catalog, LLM agent integration, React, TypeScript, Git / CI-CD

Secondary tech stack:

Pydantic, Async Python, Pytest, MLflow, Delta Lake, State management, Figma-to-code

Job Title: AI-Native Full-Stack Developer Experience: 3+ years Location: Hyderabad, India (Hybrid) Type: Full-time About the Role Build and deliver SaaS platforms, web applications, and mobile apps using an AI-native development approach at Incepteo Labs. You'll work with LLMs, generative AI frameworks, and modern full-stack technologies to ship secure, production-grade products for global customers. This role is for a hands-on developer who thrives in a fast-paced environment, writes clean and secure code, and is passionate about leveraging AI to build better products faster. You'll collaborate with experienced leads and global clients to deliver solutions that scale. What You'll Do • Build and deliver full-stack solutions — SaaS platforms, web apps, and mobile applications — using an AI-native development approach • Develop AI-powered features using LLMs, RAG pipelines, agentic AI patterns, and frameworks such as LangChain and LangGraph • Implement secure payment gateway integrations, subscription billing, and pricing plan management across products • Write high-quality, secure code with a strong focus on cybersecurity — addressing OWASP vulnerabilities, data protection, and secure authentication patterns • Collaborate with global customers and internal teams via clear documentation, video calls, and presentations • Embed AI tools across the development lifecycle — code generation, testing, documentation, and deployment • Stay current with AI/ML trends, LLM advancements, and emerging security threats What We're Looking For • 3+ years of full-stack development experience with shipped products • Proficiency in modern stacks — React, Python, Node.js, TypeScript, and cloud platforms (AWS/GCP/Azure) • Hands-on experience with LLMs, generative AI, and frameworks like LangChain, LangGraph — understanding of RAG, context management, memory, and prompt engineering • Experience integrating payment gateways (Stripe, Razorpay, or similar) and building pricing/subscription models • Strong understanding of cybersecurity principles — secure coding practices, vulnerability assessment, OWASP Top 10, and data protection • Good communication skills — comfortable on client calls and writing clear documentation • Experience working in a startup or fast-paced environment • Self-starter with curiosity for emerging technologies and AI trends Why Incepteo Labs Incepteo Labs is a digital and AI innovation partner with a presence across the UK, India, USA, and Europe. You’ll be joining a fast-growing company that brings together startup agility with enterprise-grade delivery standards. At Incepteo, we believe in ownership, collaboration, and bringing ideas to life. Creative, energetic global company with a portfolio of exciting brands

Role Overview

We are looking for a skilled Python Full Stack / Agentic AI Engineer to design, develop, and deploy AI-powered applications and intelligent agentic workflows. The ideal candidate should have strong expertise in Python, FastAPI, LLMs, RAG, LangChain/LangGraph, and modern full-stack development.

You will work on building scalable backend services, integrating Large Language Models, developing AI agents, implementing Retrieval-Augmented Generation (RAG) pipelines, and creating production-ready AI applications.

Key Responsibilities

• Design and develop scalable backend applications using Python and FastAPI.
• Build and deploy Agentic AI solutions using LLMs and agent frameworks.
• Develop multi-step and multi-agent workflows using LangChain and LangGraph.
• Design and implement RAG (Retrieval-Augmented Generation) pipelines.
• Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models.
• Develop prompt engineering strategies and structured LLM workflows.
• Work with vector databases and embedding models for semantic search and knowledge retrieval.
• Build APIs and microservices for AI-powered applications.
• Integrate AI services with databases, third-party APIs, and enterprise systems.
• Develop conversation memory, tool calling, function calling, and agent orchestration capabilities.
• Implement evaluation, monitoring, logging, guardrails, and error handling for AI applications.
• Optimize applications for performance, scalability, reliability, and cost.
• Collaborate with product managers, frontend developers, data engineers, and other stakeholders.
• Write clean, maintainable, well-tested, and production-ready code.
• Participate in architecture discussions, code reviews, testing, and deployment activities.

Required Skills

Programming & Backend

• Strong proficiency in Python.
• Hands-on experience with FastAPI, REST APIs, and backend development.
• Strong understanding of asynchronous programming, API design, authentication, and middleware.
• Experience with SQL/NoSQL databases.

Generative AI / Agentic AI

• Strong understanding of LLMs and Generative AI.
• Hands-on experience building AI Agents / Agentic AI applications.
• Experience with LangChain and/or LangGraph.
• Knowledge of agent orchestration, tool calling, function calling, memory, and workflow management.
• Strong understanding of prompt engineering.

RAG

• Experience designing and implementing RAG architectures.
• Knowledge of document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.
• Experience with vector databases such as FAISS, Chroma, Pinecone, Weaviate, Qdrant, or similar.

LLM & AI Integration

• Experience integrating commercial or open-source LLMs.
• Understanding of embeddings, context windows, temperature, token usage, and model selection.
• Experience with structured outputs and LLM-based workflows.
• Familiarity with LLM evaluation and observability is a plus.

Full Stack

• Working knowledge of HTML, CSS, JavaScript/TypeScript.
• Experience with React.js or similar frontend frameworks is preferred.
• Ability to integrate frontend applications with Python/FastAPI services.

AI Engineer

Focus: Agentic AI, AI Shopping Assistants & Virtual Try-On

Role Summary :

We are looking for a Full-Stack AI Engineer to build, deploy, and operate production-grade AI applications, including agentic shopping assistants and multimodal AI experiences. The role requires strong hands-on expertise in Python, TypeScript, LLM-based applications, real-time streaming, evaluation, and cloud infrastructure.

The ideal candidate can independently deliver end-to-end features across backend agent runtimes and frontend interfaces, with a strong focus on reliability, latency, cost optimisation, and production performance.

Key Responsibilities :

• AI Agent Development: Build and maintain Python-based agent runtimes using LLMs, tool calling, structured outputs, retrieval-augmented generation (RAG), multi-turn state, and human escalation workflows.
• Full-Stack Engineering: Develop asynchronous Python APIs and TypeScript web components, implementing server-sent events (SSE), streaming interfaces, interactive product cards, and resilient client-side error handling.
• LLM Evaluation: Build evaluation datasets and automated test harnesses using deterministic and model-based graders, regression gates, ablation studies, and pass@k/pass^k metrics.
• Performance & Cost Optimisation: Improve response latency, time to first token, token consumption, caching efficiency, context management, and cost per conversation.
• Production Operations: Implement distributed tracing, structured logging, LLM observability, monitoring, incident resolution, feature flags, controlled rollouts, and rollback mechanisms.
• Cloud & DevOps: Deploy containerised services, manage CI/CD pipelines, infrastructure as code, and production workloads on cloud platforms.
• E-commerce AI Integration: Integrate product search, catalogue data, product details, grounded recommendations, and commerce-related event tracking into AI-powered shopping experiences.
• Virtual Try-On & Multimodal AI: Contribute to image-based generative AI applications, including embeddable frontend widgets and scalable backend services.
• Internationalisation & Scalability: Support multilingual experiences, brand-specific configurations, localisation, currency handling, and backward-compatible integrations.
• Cross-Functional Collaboration: Work with product, business, and engineering stakeholders to troubleshoot quality issues and deliver measurable improvements to customer experience and business outcomes.

Essential Skills & Experience :

• Strong hands-on experience with Python and TypeScript.
• Production experience building LLM-powered applications using tool/function calling, structured outputs, streaming, retries, context management, and RAG.
• Strong understanding of asynchronous Python, REST APIs, SSE, and event-driven communication.
• Practical experience designing LLM evaluation frameworks, test datasets, automated graders, regression testing, and evaluation metrics.
• Experience deploying and operating cloud-based applications, containerised services, CI/CD pipelines, and infrastructure as code.
• Familiarity with production observability, distributed tracing, structured logging, performance monitoring, and incident management.
• Experience with caching, latency optimisation, token and inference cost management, feature flags, and safe deployment strategies.
• Strong software engineering fundamentals, debugging skills, and end-to-end ownership of production features.

Preferred Skills :

• Experience with agent frameworks such as Google ADK, LangGraph, or Claude Agent SDK.
• Hands-on exposure to Google Cloud Platform, Vertex AI, Gemini, FastAPI, and Cloud Run.
• Experience with frontend frameworks and tools such as Lit, Next.js, esbuild, and Vitest.
• Familiarity with PostgreSQL, BigQuery, OpenTelemetry, Opik, and LLM tracing platforms.
• Knowledge of MCP servers, sub-agents, agent-to-agent integrations, and retrieval systems.
• Experience with e-commerce search, multimodal AI, image generation, virtual try-on, and third-party web embeds.
• Understanding of prompt-injection mitigation, multilingual applications, and inference performance optimisation.
• Effective use of AI coding assistants and developer productivity tools.

Role Expectations :

• Deliver production-ready features across both backend AI services and frontend applications.
• Demonstrate evaluation evidence, observability, and safe rollout practices for AI-driven changes.
• Balance response quality, reliability, latency, infrastructure costs, and user experience.
• Work effectively within existing systems, maintaining backward compatibility and planning migrations and rollbacks.
• Take ownership of troubleshooting, continuous improvement, and production reliability.

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.

Key Responsibilities

• Design, develop, and maintain scalable Python backend applications for enterprise use cases.
• Develop robust REST APIs and microservices using Python frameworks such as FastAPI, Flask, or Django.
• Design and implement scalable backend services with proper API integration, authentication, error handling, logging, and monitoring.
• Develop responsive and scalable React.js frontend applications.
• Implement React Hooks, state management, API integration, reusable components, and frontend development.
• Integrate React.js applications with Python backend APIs and microservices.
• Design and develop Generative AI and LLM-powered applications.
• Build and integrate Agentic AI / AI Agent solutions for enterprise use cases.
• Develop RAG (Retrieval-Augmented Generation) pipelines using enterprise data and knowledge sources.
• Work with embeddings, vector databases, and vector search for semantic retrieval and knowledge-based applications.
• Develop AI agent workflows using frameworks such as LangChain, LangGraph, Google ADK, or Semantic Kernel.
• Implement tool calling and function calling to enable AI agents to interact with APIs, databases, enterprise systems, and external services.
• Apply prompt engineering techniques to improve LLM response quality, accuracy, consistency, and reliability.
• Integrate LLMs and GenAI capabilities into full-stack applications.
• Develop multi-step AI workflows, agent orchestration, and intelligent automation solutions.
• Design APIs and services for seamless integration between AI components, backend services, databases, and frontend applications.
• Work with cloud platforms such as AWS, Azure, or GCP for application and AI solution deployment.
• Develop production-ready applications with focus on scalability, performance, security, reliability, and maintainability.
• Troubleshoot and optimize backend, frontend, API, RAG, LLM, and Agentic AI components.
• Collaborate with architects, software engineers, AI/ML engineers, product teams, and business stakeholders.
• Participate in code reviews, technical discussions, testing, deployment, and production support.

Mandatory Skills

• Python Backend Development
• REST API / Microservices
• FastAPI / Flask / Django
• React.js
• React Hooks / State Management
• Frontend Development & API Integration
• GenAI / LLM
• Agentic AI
• RAG
• Embeddings / Vector Search
• LangChain / LangGraph / Google ADK / Semantic Kernel
• Prompt Engineering
• Tool Calling / Function Calling
• Cloud – AWS / Azure / GCP

Preferred Candidate Profile

• 8.5+ years of overall software development experience.
• Strong hands-on experience in Python backend development and API/microservices development.
• Strong experience in React.js and full-stack application development.
• Practical experience building GenAI/LLM applications.
• Hands-on experience with Agentic AI and AI agent frameworks.
• Good understanding of RAG, embeddings, vector search, and LLM-based application architecture.
• Experience with LangChain, LangGraph, Google ADK, Semantic Kernel, or equivalent agent frameworks.
• Strong understanding of prompt engineering and tool/function calling.
• Experience integrating AI capabilities with APIs, databases, enterprise applications, and external systems.
• Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
• Strong problem-solving, debugging, communication, and collaboration skills.
• Candidates should be available for immediate / short-term joining.

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.