Platform Engineer Agentic AI Job at Levy Professionals (Utrecht)

Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services)

Location

United States , New York; San Francisco; San Jose; Cambridge; McLean

Salary:

197300.00 - 245600.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
At least 4 years of experience programming with Python, Go, Scala, or Java

Job Responsibility

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One

What we offer

performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits

Fulltime

Sr. Distinguished AI Engineer (Agentic AI Platform)

At Capital One, we are creating responsible and reliable AI systems, changing ba...

Location

United States , San Jose, California; San Francisco, California

Salary:

343400.00 - 392000.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing AI and ML algorithms or technologies
At least 10 years of experience programming with Python, Go, Scala, or Java
9 years of experience deploying scalable and responsible AI solutions on cloud platforms
2+ years of experience supporting Agentic Frameworks
2+ years of experience with LLMOps
8+ years of experience designing mission-critical machine learning platforms
2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level
Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, or Golang
Master's degree in Computer Science, Computer Engineering, or relevant technical field

Job Responsibility

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
Contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs
Standardizing and automating agentic workflows
Contribute to crafting an end to end GenAI SDK, CLI and starter kits
Help bring together a vision of central guardrail services
Collaborate with cross organization architects to drive end to end performance
Accelerate innovation by incubating proof of concepts and driving RFCs
Own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs
Coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences

What we offer

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits

Fulltime

GCP AI Platform Architect / Lead AI Platform Engineer

Our client is an innovative technology company specializing in the development o...

Location

Poland , Kraków

Salary:

Not provided

TeamQuest Sp. z o. o.

Expiration Date

Until further notice

Requirements

GCP Expertise (verifiable - ask for production examples): GCP is their primary cloud not secondary experience alongside AWS/Azure. Production deployments across most of: Vertex AI, Cloud Run or GKE, Pub/Sub, BigQuery, Secret Manager, VPC Service Controls, IAM + Workload Identity. Has designed for GCP from scratch, not migrated from another cloud, end-to-end ownership
AI / Backend Engineering: Python is the primary language - production-grade service/API development, not scripting or data science only. Strong track record building distributed systems and integrating LLMs.
Agentic Architecture (must be production, not PoC): Hands-on production experience with at least one: LangGraph, Google ADK, CrewAI, or custom multi-agent orchestration layer. RAG pipelines shipped to production. Google ADK: candidate must be able to explain what it is, when to use it, and how it compares to LangGraph and custom orchestration. AI agent workflows, ReAct prompting, and Function Calling in production environments
Multi-Tenant Architecture: Has designed a multi-tenant SaaS platform end-to-end - not just contributed. Can articulate tenant isolation strategies: IAM boundary design, data isolation per tenant, VPC controls.
API Design & Integrations: Proven ability to create secure, high-performance APIs capable of asynchronously managing traffic and communication between multiple decoupled services.
Enterprise Security: Practical knowledge of data isolation in multi-tenant SaaS architectures, IAM, and securing cloud-based environments.
Vector Databases: Hands-on experience with semantic search and at least one of: Pinecone, Weaviate, pgvector, or Vertex Matching Engine.

Job Responsibility

System Architecture: Design and develop a scalable, cloud-native architecture on Google Cloud Platform (GCP) that meets enterprise security and multi-tenant data isolation requirements for a SaaS environment
AI Agent Orchestration: Architect and implement autonomous, multi-step AI workflows with a clear separation of agent responsibilities (retrieval, analysis, reasoning, response generation)
Hands-on Core Development: Actively contribute to core system development-coding orchestration logic, designing services, optimizing performance, and building secure API integrations for routing queries across internal and external agents
Frontend Enablement: Design the backend layer, streaming protocols, and APIs to seamlessly support and integrate with advanced conversational UIs
Data Management & Extensibility: Build a robust backend capable of processing qualitative and social data, ensuring the platform is easily extensible to incorporate new data sources

What we offer

Attractive salary
Full remote work
Social benefits:sporto card,healthcare insurance

Fulltime

GCP AI Platform Architect / Lead AI Platform Engineer

Our client is an innovative technology company specializing in the development o...

Location

Poland , Katowice

Salary:

Not provided

TeamQuest Sp. z o. o.

Expiration Date

Until further notice

Requirements

GCP Expertise (verifiable - ask for production examples): production deployments across most of: Vertex AI, Cloud Run or GKE, Pub/Sub, BigQuery, Secret Manager, VPC Service Controls, IAM + Workload Identity
Has designed for GCP from scratch, not migrated from another cloud, end-to-end ownership
AI / Backend Engineering: Python is the primary language - production-grade service/API development, not scripting or data science only
Strong track record building distributed systems and integrating LLMs
Agentic Architecture (must be production, not PoC): Hands-on production experience with at least one: LangGraph, Google ADK, CrewAI, or custom multi-agent orchestration layer
RAG pipelines shipped to production
Google ADK: candidate must be able to explain what it is, when to use it, and how it compares to LangGraph and custom orchestration
AI agent workflows, ReAct prompting, and Function Calling in production environments
Multi-Tenant Architecture: Has designed a multi-tenant SaaS platform end-to-end - not just contributed
Can articulate tenant isolation strategies: IAM boundary design, data isolation per tenant, VPC controls

Job Responsibility

System Architecture: Design and develop a scalable, cloud-native architecture on Google Cloud Platform (GCP) that meets enterprise security and multi-tenant data isolation requirements for a SaaS environment
AI Agent Orchestration: Architect and implement autonomous, multi-step AI workflows with a clear separation of agent responsibilities (retrieval, analysis, reasoning, response generation)
Hands-on Core Development: Actively contribute to core system development-coding orchestration logic, designing services, optimizing performance, and building secure API integrations for routing queries across internal and external agents
Frontend Enablement: Design the backend layer, streaming protocols, and APIs to seamlessly support and integrate with advanced conversational UIs
Data Management & Extensibility: Build a robust backend capable of processing qualitative and social data, ensuring the platform is easily extensible to incorporate new data sources

What we offer

Attractive salary
Full remote work
Social benefits: sport card, healthcare insurance

Fulltime

Senior AI Engineer (Agentic AI / LLM Engineering)

We’re partnering with a rapidly growing, innovation-focused organization that is...

Location

United States

Salary:

Not provided

Zeektek

Expiration Date

Until further notice

Requirements

5+ years of experience in software engineering, data engineering, or AI/ML engineering
Hands-on experience building applications using LLMs (e.g., GPT, open-source models)
Experience with agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI, or similar)
Strong programming skills in Python
Experience working with large datasets and distributed data platforms
Familiarity with Databricks or similar modern data platforms
Experience building production-grade AI systems (not just POCs)
Strong understanding of prompt engineering and LLM optimization techniques

Job Responsibility

Design and build agentic AI systems leveraging large language models (LLMs)
Develop scalable AI solutions using modern data and AI platforms (Databricks preferred)
Translate business problems into production-ready AI workflows and applications
Collaborate with product and architecture teams to define AI use cases and technical approaches
Implement and optimize: Prompt engineering strategies
Token usage and cost efficiency
Model performance and response quality
Work with large-scale datasets to support training, fine-tuning, and inference workflows
Contribute to the development of AI engineering standards, frameworks, and best practices
Partner with data science teams to integrate models into production environments

What we offer

Weekly Direct Deposit
401K Matching
Competitive medical, dental and vision insurance
Consistent communication throughout your project
ZeekTek Referral Program

Senior AI Engineer (Agentic AI)

High-autonomy role focused on the deployment, maintenance, and evolutionary scal...

Location

Singapore , Singapore

Salary:

8000.00 - 9000.00 SGD / Month

Randstad

Expiration Date

July 27, 2026

Requirements

At least 5 years of experience in machine learning, system deployment, or semiconductor automation
Proven expertise in GenAI workflows, including prompt engineering, PEFT/LoRA fine-tuning, RAG, and multi-agent frameworks
Technical proficiency in Python and libraries such as PyTorch, TensorFlow, and OpenCV is required
Strong understanding of SQL, big data architectures, Git, Docker, and cloud platforms like AWS, Azure, or GCP

Job Responsibility

Lead the design, deployment, and integration of autonomous AI systems for multi-step reasoning and automated workflows within the fab ecosystem
Monitor production performance, manage retraining pipelines, and address data drift or anomalies
Fine-tune LLMs and computer vision frameworks using equipment metadata for failure triage, yield assistance, and hardware accuracy
Partner with IT to orchestrate scalable SQL/Big Data pipelines while ensuring strict data governance
Provide architectural guidance and mentorship on scaling and deploying robust AI/ML systems

Staff AI Engineer - Agentic AI Systems

As a Staff AI Engineer, you will play a key role in designing and delivering hig...

Location

India , Bengaluru, Karnataka, India | Hyderabad, Telangana, India | Pune, Maharashtra, India

Salary:

Not provided

Teradata

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science or equivalent from a recognized institution
8+ years of experience in backend services, distributed systems, or data platform development
Strong proficiency in Java, Go, or Python for service development
Deep understanding of design principles, distributed system patterns, and service architecture
Hands-on experience designing and developing RESTful APIs
Experience with SQL and NoSQL databases and data modelling
Strong debugging, problem solving, and troubleshooting skills
Experience with modern containerization and orchestration tools such as Kubernetes
Knowledge of public cloud platforms
Experience with AI productivity tools (e.g., GitHub Copilot)

Job Responsibility

Design, architect, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance
Collaborate with cross-functional engineers and product partners to shape architecture and consistently deliver end to end features
Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability
Work with SQL and NoSQL databases to implement efficient data models and service access patterns
Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs)
Use AI powered engineering tools to improve development quality, speed, and productivity
Mentor engineers, supporting them in technical planning, implementation, and best practices
Identify and resolve system performance bottlenecks, optimizing code, architecture, and infrastructure
Write unit and integration tests and participate in code reviews to uphold engineering excellence
Investigate production issues, ensuring timely and effective solutions

Fulltime

Full Stack Engineer (AI & Agentic AI Systems)

The Full Stack Engineer (AI & Agentic AI Systems) is a strategic professional wh...

Location

India , Pune; Chennai

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

2-5 years in an Apps Development role
Demonstrated execution capabilities
Strong analytical and quantitative skills
Data driven and results-oriented
Experience in running high traffic, distributed, cloud based services
Experience in affecting large culture change
Experience leading infrastructure programs
Skilled at working with third party service providers
Excellent written and oral communication skills
Bachelor’s/University degree or equivalent experience

Job Responsibility

Design and deliver end‑to‑end solutions spanning architecture, system design, low‑level design, and high‑quality coding across modern full‑stack environments
Build responsive, modular UI applications using React, integrating complex AI-driven workflows and real‑time interactions
Develop scalable, high‑performance backend services in Java / Python, implementing resilient APIs, event‑driven patterns, and microservices architectures
Engineer AI‑powered features leveraging Google Gemini LLM, Vertex AI, ADK, vector databases (A2A), RAG pipelines, MCP, context engineering, and advanced prompt engineering techniques
Implement secure, well‑structured REST and GraphQL APIs, ensuring reliability, versioning discipline, and clean integration patterns across platforms
Optimize system performance and scalability, applying profiling, load‑testing insights, caching strategies, and distributed system tuning
Drive robust CI/CD practices, integrating automated testing, code quality gates, containerization, and cloud‑native deployment pipelines
Partner with QE to build and maintain automated test suites (UI, API, integration, and performance), improving release quality and reducing regression risk
Identify, diagnose, and remediate performance bottlenecks, penetration testing vulnerabilities, and production issues with precision and root‑cause clarity
Collaborate cross‑functionally with AI scientists, architects, and product teams to translate business challenges into production‑ready, intelligent agentic systems

Fulltime

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Platform Engineer Agentic AI

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