Title: AI Architect Claude Code Senior Developer - Job Opening IDBZ_772_JOB - Salary & Package$160K-$220K base, bonus, benefits - IndustryTechnology - Job TypePermanent - Skills RequiredAI, Agentic, Architect - Education/QualificationsIT Degree or Masters - CategoryApplication Development - Right to Work in CountryUSA Citizen - CityRemote USA - State/ProvinceAny - CountryUnited States - Zip/Postal Code10001 About Us Advisory, Executive Search, Senior Appointments, Interim Management Consultants Job Description AI Architect, US-Based (Remote) to build AI systems that work in production - not demos, not chatbots, not hype. We are conducting a confidential search for an experienced AI Business, Solutions and Technical Architect to join a scaled, high-growth US consumer digital business. This role is for a former senior software engineer who now designs and builds production-grade, agentic AI systems. You will not be prompting and hoping for the best. You will be architecting the harness around the model so AI can reliably execute multi-step workflows at scale. The Mission Your mandate is to turn AI into a reliable operating system for the business. Work will progress across three levels: Level 1: Automate operational processes Level 2: Automate complex but binary workflows (clear right/wrong outcomes) Level 3: Apply AI to creative, non-binary work with verification, control, and measurement Success is defined by measurable wins, not impressive demos What You Will Do Architect and build agentic AI systems using Claude Code Design the AI harness, including: State management Context management (preventing context rot) Tool orchestration Error recovery strategies Verification and validation loops Failure reflection and learning Define SOPs and system logic before building agents Apply context engineering (ACE) so AI receives only what it needs — no more, no less Convert non-binary business problems into binary, measurable questions Ensure continuous improvement, performance tracking, and cost optimization Act as the bridge between product vision and technical execution Required Background Be US-based (remote within the US) Have a strong background as a software engineer / senior developer Have hands-on production experience with Claude Code Understand that AI ≠ chat Be able to clearly define a “win” and measure it Strong experience across: LLM & reasoning model fundamentals Agentic system design and orchestration APIs, integrations, data architecture, and security Python, TypeScript / JavaScript, SQL Cloud platforms (AWS, GCP, or Azure) How You Think Build systems and SOPs before agents Prefer principles over tools Avoid over-engineering Read source material, not shiny YouTube summaries Can deliver an actionable, measurable improvement within 48 hours Red flags we screen out: Vague specifications Tool or framework zealotry Cool demos that don’t survive production Research-only or academic profiles Over-engineered solutions Compensation & Benefits Bonus: 10–20% annual performance bonus Based on company results and individual system impact Benefits include: Medical, dental, vision insurance 401(k) with employer contribution Generous PTO and holidays Fully remote (US-based) Home office / equipment allowance Base Salary: $160,000 – $220,000 USD What Success Looks Like (6–12 Months) Multiple AI systems running in production High multi-step success rates across workflows Measurable operational or revenue impact AI treated as infrastructure, not experimentation

Title: AI Software Engineer Location: (Remote – United States, Canada) Full time Remote Job Description: Salary: $170K - $190K USD Role Overview Join a fast-growing company revolutionizing how science is communicated by enabling researchers to create professional scientific graphics quickly and easily. Often referred to as the Adobe or Canva for science, this company is on a mission to accelerate scientific discovery. With $17.04M in funding and a global presence, it is leveraging AI to further enhance its platform, ensuring scientists can visualize complex data with ease and precision. Responsibilities: Design and implement AI-powered solutions that enhance the scientific visualization platform. Collaborate with product and engineering teams to integrate AI into user-facing features and internal workflows. Develop scalable, AI-driven applications using modern JavaScript frameworks and Python. Optimize AI/ML models for performance, reliability, and scalability in production environments. Build APIs and implement AI/LLM-based solutions beyond basic coding assistants like Copilot or Cursor. Work across multiple codebases and technical domains without requiring extensive onboarding. Translate business requirements into technical solutions, ensuring seamless AI adoption in production workflows. Compensation: United States: ▪ $170K - $200K USD (Bay Area, Seattle, New York) ▪ $170K - $190K USD (Other US locations) Canada: ▪ $160K - $180K CAD Requirements: ✔ 7-12 years of full-stack software engineering experience, with expertise in JavaScript (modern frameworks) and Python. ✔ Proven experience integrating AI/ML models into production applications and AI-powered product development. ✔ Strong product engineering background, working closely with product teams on user-facing features. ✔ Preference for engineers who started in software engineering and later incorporated AI/ML into their work. ✔ Experience working on AI-native products, contributing to core functionalities. ✔ Familiarity with APIs for AI services (e.g., OpenAI) or experience implementing open-source models into production. ✔ Strong ability to explain technical concepts to non-technical stakeholders. ✔ Experience with cloud infrastructure (AWS preferred) for AI/ML-driven applications. Do Not Apply If You: Require visa sponsorship (H1B, TN, etc.). Have a history of frequent short tenures (job hopping). Have only worked in big corporations (Uber, Intel, etc.) without startup experience. Come from an IT consulting background (Infosys, Tata, Capgemini, Cognizant, Wipro, etc.). Graduated from coding bootcamps (Full Stack Academy, Hack Reactor, etc.). Have fake or misrepresented profiles.

Role Description - 6-8 years of hands-on experience with Generative AI, AI, ML, and Data Science technologies. - Extensive hands-on experience in implementing end-to-end projects utilizing Generative AI. - Experience in building production-grade solutions utilizing Generative AI as well as AI and ML components. - Extensive hands-on experience in building Generative AI applications using methodologies such as: - RAG - Prompt engineering - Embedding - Fine-tuning - Experience in working with structured as well as unstructured data for building RAG-based solutions. - Experience with AI, ML search, and data services within the GCP ecosystem such as: - GCP Vertex AI - Vertex AI Vector Search - Gemini - Cloud Run - Cloud SQL - Experience with agent frameworks such as: - Google ADK - Langgraph - CrewAI - Hands-on experience in working with cloud AI services: - GCP Vertex AI - Azure AI - AWS Bedrock - Extensive experience in Python programming languages along with popular frameworks such as: - Flask - FastAPI - Experience with AIML, deep learning, TensorFlow, Python, and NLP. - Excellent understanding of Generative AI related concepts, methodologies, and techniques. Qualifications - Bachelor's degree in computer science or related field. - 5 years AIML experience including 2 years in GenAI projects. - Proficiency with Azure AI services and Python. - Experience with agent-based frameworks such as LangChain and LangGraph is highly desirable. - Solid understanding of API integration, test automation, and software engineering principles. - Good teamwork and communication skills. Requirements - Mandatory Skills: - MLOPS - GenAI - LLMOps - Machine Learning - AIOPS

Role Description We're partnering with an AI-driven technology company looking to hire an AI Knowledge Graph/ Ontology Lead to build and scale the knowledge graph layer underpinning a new generation of intelligent enterprise products. This is a senior, hands-on leadership role for someone who has real experience designing and shipping production knowledge graphs, not just conceptual ontology work. You'll be responsible for shaping a graph and ontology platform that powers: - AI retrieval and RAG workflows - Entity linkage and reasoning systems - Cross-domain and temporal knowledge modeling - Regulatory and compliance intelligence products - Agentic AI applications The role combines architecture, hands-on engineering, and team leadership. You'll work closely with AI/ML engineers to turn complex, unstructured information into structured, queryable intelligence that directly feeds live AI systems. Qualifications - Strong Neo4j and Cypher expertise in production environments - Deep ontology / taxonomy modeling experience - Python engineering skills - Knowledge graph integration with LLMs, RAG, or vector search systems - Experience balancing formal semantics with pragmatic implementation - Ability to lead technically while remaining hands-on Requirements - Additional experience in areas such as RDF/OWL, inference engines, entity resolution, legal/regulatory data, ESG, healthcare, or pharmaceutical domains would be highly valuable. Benefits - A highly technical AI environment - Significant ownership and architectural influence - Fast decision-making and direct access to leadership - Strong adoption of AI-assisted development tooling - Flexible working arrangements and competitive compensation Company Description Ideal for someone excited by the challenge of building the intelligence layer behind complex AI products at scale. Please apply for more details.