We are looking for an experienced GenAI Senior Engineer to design, build, and maintain scalable, secure, and production-grade AI platforms and applications.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $120,000-$150,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.
Responsibilities
Design, develop, and maintain scalable, secure, and highly available GenAI platforms and AI-powered applications on AWS.
Architect and implement Agentic AI solutions, multi-agent systems, tool integrations, function calling, and workflow orchestration frameworks.
Design and implement enterprise-grade RAG solutions using embeddings, vector databases, semantic search, reranking, and knowledge retrieval techniques.
Build AI applications leveraging Amazon Bedrock for LLM inference, model orchestration, prompt management, and foundation model integrations.
Develop reusable AI platform components, SDKs, APIs, accelerators, and reference architectures.
Senior AI Architect responsible for designing and governing generative AI solutions across Wind Engineering.
Compensation
For candidates applying to a U.S. based position, the pay range for this position is between $113,200.00 and $188,800.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas.
Responsibilities
Define the Generative AI Architecture for Wind Engineering
Establish approved patterns for model gateways, prompt and context management, retrieval, memory, tool invocation, orchestration, evaluation, logging, and user experience
Define selection criteria for hosted, enterprise, open-weight, fine-tuned, and task-specific models
Ensure solutions align with approved GE Vernova platforms, identity, data, integration, and deployment standards
Design Agentic and Tool-Integrated Workflows
Requirements
Bachelor's degree in Computer Science, Engineering, Applied Mathematics, Data Science, or a related technical field
Senior AI Architect responsible for designing, evaluating, and integrating generative AI solutions across Wind Engineering.
Compensation
For candidates applying to a U.S. based position, the pay range for this position is between $113,200.00 and $188,800.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas.
Responsibilities
Define Generative AI Architecture for Wind Engineering
Establish reference architectures for foundation-model applications, RAG, tool-using assistants, agentic workflows, document intelligence, and multimodal engineering use cases
Establish approved patterns for model gateways, prompt and context management, retrieval, memory, tool invocation, orchestration, evaluation, logging, and user experience
Define selection criteria for hosted, enterprise, open-weight, fine-tuned, and task-specific models
Ensure solutions align with approved GE Vernova platforms, identity, data, integration, and deployment standards
Requirements
Bachelor's degree in Computer Science, Engineering, Applied Mathematics, Data Science, or a related technical field
Design, build, and ship production‑grade AI applications using Claude and other LLMs, manage AI asset platform, and govern AI skills and plug‑ins within a regulated enterprise.
Compensation
The expected salary range for this position is $ 135,000 to $160,000 and will be impacted by factors such as the successful candidate’s skills, experience and working location, as well as the specific position’s business line, scope and level.
Responsibilities
Build reusable skills and package them as plug‑ins
Configure and tune foundational models
Build retrieval‑augmented generation, embeddings, and multi‑step workflows
Take prototypes and productionize them
Own and govern the skill and plug‑in marketplace
Requirements
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field
Nice to have: Agent development and orchestration (LangGraph, CrewAI, Claude Agent SDK)
Lead the AI Engineering function as a senior technical individual contributor, establishing standards, governance, and technical direction for AI skills, plug‑ins, and enterprise AI applications.
Compensation
The expected salary range for this position is $ 130,000 to $190,000 and will be impacted by factors such as the successful candidate’s skills, experience and working location, as well as the specific position’s business line, scope and level.
Responsibilities
Build reusable skills and plug‑ins for AI applications
Configure and tune foundational models for HUB use cases
Build retrieval‑augmented generation, embeddings, vector store, and multi‑step workflow implementations
Productionize AI prototypes into reliable, governed applications
Define and document engineering standards
Requirements
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field
Nice to have: Agent development and orchestration (LangGraph, CrewAI, Claude Agent SDK)
As a Senior ML Engineer focused on Search Optimization, you will work on improving the quality of our search product across the all parts of the search stack. This is an applied ML and information-retrieval role combining experimentation with production impact.
Responsibilities
Design, implement, and operate the retrieval system for a search vertical
Connect and tune the data pipeline, from ingestion to relevance tuning
Build knowledge-graph and entity-resolution layers: entity linking / NER, ontologies, and graph databases (Neo4j or similar)
Develop structured-extraction pipelines over unstructured domain data
Reason about freshness and trust: model how confident we are in a fact and how stale it has become before we serve it
Client‑embedded builder‑advisor converting high‑value enterprise AI opportunities into secure, reliable and production‑ready agentic systems.
Responsibilities
Diagnose and prioritize workflows where agentic AI can materially improve cost‑to‑serve, cycle time, throughput, revenue leakage or total cost of ownership
Partner with CEOs, COOs, CDOs, CTOs, CISOs, CFOs and business leaders to shape the value case, delivery scope, adoption model and measurable outcomes
Build working 0→1 prototypes rapidly and convert validated concepts into production systems rather than presentation‑only deliverables
Design and implement multi‑agent architectures, including planner–executor patterns, agent handoffs, durable state, checkpointing, retries, cancellation and human‑in‑the‑loop escalation
Implement Model Context Protocol (MCP), agent‑to‑agent interoperability, model routing, fallback and hybrid pipelines across LLMs, SLMs and traditional ML components
Requirements
Bachelor’s or master’s degree in Computer Science, Engineering, or another quantitative discipline
BE/BTech/MTech/MCA or equivalent qualifications
Nice to have: Knowledge graph
Nice to have: ontology
Nice to have: semantic‑layer experience using Neo4j
Senior Data Scientist (m/w/d), Agentic AIAlexander Thamm GmbH · München, Germany+5 more
Senior ML Engineer, Search Optimization (Agentic Search)Tavily · Tel Aviv, Israel