Support the development of data-driven solutions, analytics and reporting capabilities, design, develop and maintain scalable backend services and APIs, build AI/LLM solutions, and contribute to data science and automation projects.
Responsibilities
Design, develop and maintain scalable backend services and APIs using Python, Flask and FastAPI
Build production-ready AI/LLM solutions, including REST APIs, WebSocket streaming, authentication and integration with external systems
Develop and optimize Large Language Model (LLM) applications using GPT and open-source models
Build and maintain RAG pipelines, vector search solutions and AI agent workflows
Integrate internal and external data sources, databases and APIs into AI-powered applications
Front‑end web developer focused on HTML5, CSS3, JavaScript (jQuery) and AI‑driven web development and QA solutions for WebMD’s health information platforms.
Responsibilities
Create cross‑browser/device fully functional web pages using HTML5, CSS3, and JavaScript (jQuery), adhering to accessibility and W3C web standards
Verify quality of web products, log defects, implement changes, and re‑verify defects independently
Serve as a technical liaison between the Web and QA teams
Translate wireframes/PSDs/Figma files into launch‑ready, valid HTML/CSS/JS
Design, code, test, defect manage, and support production in collaboration with internal teams
Requirements
B.E. Computer Science/IT degree (or any other engineering discipline)
Pre‑Sales Solution Architect who designs and validates practical solutions, builds customer confidence, and shapes the HiBob platform and ecosystem.
Compensation
Cash allowance for health insurance - £4,200 yearly
Responsibilities
Build customer confidence and drive revenue
Partner with Account Executives and Sales Engineers to lead technical discovery, uncover business priorities, and guide customers through complex architecture decisions
Design and validate practical solutions, resolve technical blockers, and give implementation teams a clear handoff of agreed designs and requirements
Connect systems, AI, and people context
Design integration solutions across Bob and the wider customer ecosystem using APIs, webhooks, identity services, and automation platforms
Senior Platform Engineer focused on designing, integrating, and operationalizing AI agents and agentic workflows within secure enterprise environments.
Locations (2)
Springfield, Virginia, United States
United States
Compensation
Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Remote - USA $148,750—$201,250 USD
Responsibilities
Design, build, and integrate AI agents and multi-agent workflows using modern LLM and agentic technologies.
Develop agent capabilities that interact with enterprise applications, APIs, data sources, developer tools, and mission systems.
Integrate models, agents, tools, and enterprise data into secure workflows that can be deployed in controlled and classified environments.
Work with LLMs, RAG, embeddings, vector databases, tool/function calling, structured outputs, MCP, and related technologies.
Develop mechanisms for agents to securely discover, access, reason over, and act upon approved enterprise data and services.
Design and evolve a biological research platform that turns experimental work into organized, accessible, analysis‑ready data.
Compensation
The salary range for this role is $74,000 - $126,500.
Responsibilities
Learn how experiments are run and how samples and results are tracked, and identify where manual handling slows progress.
Identify recurring needs, design reusable data models and workflows, and carry them through implementation, testing, and operation.
Design schemas and interfaces spanning computational screening inputs and outputs through final experimental records, connecting compute and experimental work and enabling powerful querying.
Build or orchestrate pipelines that parse heterogeneous files and records, harmonize metadata, validate results, and load shared systems, replacing repetitive manual steps with recoverable workflows across laboratory records, cloud storage, databases, and external services.
Make data available through APIs, visualizations, and AI‑enabled interfaces.
Description
We are looking for an experienced Agentic AI & ML Engineer with a strong backend development background, hands-on experience in Machine Learning (ML), Deep Learning (DL), and Multi-Agent Systems, and expertise in AI-driven automation.
The ideal candidate has practical experience building and implementing ML/DL solutions and designing multi-agent architectures in real-world projects.
Requirements
Required Experience & Skills
Minimum 3 years of backend development experience.
Strong hands-on experience with Machine Learning (ML) and Deep Learning (DL), demonstrated through previous projects.
Proven experience designing, building, and implementing Multi-Agent Systems, including agent orchestration, coordination, and communication.
Strong practical experience with Agentic AI development and AI agent architectures.
Experience developing and integrating ML/DL models into backend applications and AI-driven workflows.
Strong understanding and hands-on experience with MCP (Model Context Protocol).
Experience with automation tools and workflow platforms such as n8n.
Experience working with AI tools and LLMs such as Claude.
Experience with prompt engineering, prompt design, and prompt evaluation.
Strong understanding of workflow automation, AI agents, and backend integrations.
Ability to independently design, implement, and optimize complex AI-driven solutions.
Strong ownership mindset and problem-solving skills.
Fluency in English.
Nice to Have
Experience with Python and ML/DL frameworks such as PyTorch or TensorFlow.
Experience with multi-agent frameworks such as LangGraph, CrewAI, or AutoGen.
Experience working with AWS.
Experience with CRM systems, customer lifecycle management, retention analytics, or marketing automation platforms.
Experience deploying and maintaining production-grade ML models and AI agent systems.
Previous experience in the iGaming industry.
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