Agentic AI Senior Consultant - Europe

Enterprise AI is moving from pilots to production, and the constraint is no longer the model it's the data. Agents are only as good as what they can sense, trust, and act on in the moment, and real-time, event-driven data is becoming the foundation every serious AI system runs on.

The company is the leading platform for the enterprise AI era. Established enterprises worldwide — including RBC Capital Markets, Bosch, NSE, BSE, Airtel, HDFC, SBI , PSA Singapore, United Airlines, Schwarz Group, and hundreds more have built their business around the company to enable intelligent, real-time experiences, modernize their application and integration landscape, and create seamless digital journeys for their customers, partners, and employees.

So, the next time you drive a car, order furniture online, fly in a plane, check your bank balance on your phone, your positive experience could be a direct result of our technology and your hard work!

About the Role

As an  Agentic AI Senior Consultant , you will serve as a trusted technical advisor and hands-on builder, owning the successful design, implementation, and production adoption of agentic AI solutions built on the company Agent Mesh and the the company Platform in complex enterprise environments.

This role carries the same delivery ownership, autonomy, and customer leadership expectations as our Senior Consultant role, with a primary focus on agentic AI. You will work directly with customer engineering and business teams to identify high-value agentic use cases, design multi-agent architectures, and write the code that takes them from pilot to production. Just as the SDLC anchors software delivery, the  Agent Development Lifecycle (ADLC) anchors how you build, evaluate, release, and operate agents. You will combine deep software engineering skills, applied AI expertise, and a strong grounding in event-driven architecture to deliver agentic systems that are secure, observable, governed, and built to scale.

What You’ll Do

• Own the post-sales technical success of customers’ agentic AI initiatives, from use case discovery and solution design through build, production rollout, steady-state operations, and ongoing advisory services

• Lead use case discovery and prioritization workshops that translate customer business goals into realistic, measurable agentic workflows

• Design and build multi-agent solutions with the company Agent Mesh, including agent decomposition, orchestration and delegation patterns, tool design, memory and state management, and human-in-the-loop controls

• Write, review, and troubleshoot production-quality code in Go (our preferred language, in which the company Agent Mesh is built) or Python where customer requirements call for it, for agents, tools, plugins, and integrations, and deploy them on Docker, Kubernetes, and cloud platforms

• Connect agents to customer systems and data using MCP servers, A2A protocol, REST APIs, and event-driven integration through the the company event mesh, bridging AI with existing enterprise applications and legacy platforms

• Implement retrieval and context strategies (RAG, vector stores, knowledge bases, and real-time event context) so agents have the right information at the right time

• Apply the ADLC end to end to move solutions from prototype to production, including requirements and design, evaluation pipelines, testing, versioning, release management, monitoring, and operational runbooks

• Establish observability, guardrails, and governance for agentic systems, covering tracing, quality and accuracy evaluation, cost and latency monitoring, access control at the tool boundary, auditability, and responsible AI practices

• Advise customers on LLM selection and optimization across providers such as Anthropic, OpenAI, Google, AWS Bedrock, and Azure AI Foundry, including prompt design, token and cost management, and model trade-offs

• Act as a long-term trusted advisor , proactively identifying new agentic use cases and helping customers progress from isolated pilots to enterprise-wide, event-driven AI adoption

• Deliver recurring technical reviews, health checks, and roadmap discussions aligned to customers’ annual planning cycles

• Enable customer engineering teams to understand, extend, and take ownership of the solutions you build through pairing, workshops, and high-quality documentation

• Codify field learnings into reusable patterns, reference implementations, accelerators, and best practices that make future engagements faster and raise delivery quality across Professional Services

• Represent the voice of the customer to Product and Engineering, sharing real-world feedback that shapes the the company Agent Mesh roadmap

• Work closely with the the company Agent Mesh engineering team , collaborating on complex customer issues, validating new capabilities in real customer environments, and contributing reusable agents, plugins, and accelerators back to the the company Agent Mesh ecosystem

• Act as a technical leader and mentor , building agentic AI capability across the Professional Services team

• Communicate clearly with technical and non-technical stakeholders, explaining AI trade-offs, risks, and value in plain language and managing expectations

• Travel as required based on customer needs (including occasional international travel)

What You’ll Bring to the Role

Required Experience & Qualifications

• 7+ years of experience in professional services, consulting, system integration, forward-deployed engineering, or enterprise application development

• 2+ years of hands-on experience designing, building, and deploying LLM-based and agentic AI solutions , with at least one solution taken into production

• Proven experience applying a disciplined delivery lifecycle to agentic solutions (ADLC), with a strong foundation in SDLC practices such as version control, automated testing, CI/CD, and release management

• Strong proficiency in Go or Python , with Go strongly preferred

• Practical experience with multi-agent systems (task delegation, orchestration, coordination, and autonomous decision-making) and agent frameworks such as Google ADK, LangGraph, LangChain, CrewAI, or similar

• Experience with agent interoperability and tool integration , including MCP and A2A protocols and designing APIs as agent tools

• Solid understanding of RAG architectures , embeddings and vector databases, prompt engineering, and context management

• Experience implementing AI evaluation, observability, and guardrails for LLM applications in enterprise environments

• Solid understanding of event-driven architectures, asynchronous messaging, and integration design patterns

• Hands-on experience deploying distributed systems on Cloud-based platforms and hyperscalers like AWS, Azure, or GCP , using Docker and Kubernetes

• Knowledge of enterprise security and identity patterns relevant to AI, such as OAuth 2.0, RBAC, secrets management, and data privacy

• Ability to work independently, lead customer engagements, and make sound technical decisions with minimal guidance in a fast-evolving technology space

• Excellent written and verbal communication skills, including running workshops and presenting to senior stakeholders

• Professional fluency in English and in Spanish or Italian (written and verbal)

Preferred / Nice to Have

• Experience with the company Agent Mesh or the the company Platform

• Proficiency in both Go and Python

• Experience with messaging technologies such as the company, Kafka, RabbitMQ, ActiveMQ, IBM MQ, or TIBCO

• Working knowledge of LLM platforms such as Anthropic Claude, OpenAI, Google Gemini/Vertex AI, AWS Bedrock, or Azure AI Foundry

• Experience with LLMOps/MLOps practices, including prompt and model versioning, evaluation frameworks, and production monitoring

• Familiarity with AI governance and responsible AI frameworks and regulated-industry requirements (e.g., financial services, healthcare, public sector)

• Experience using AI-assisted and agentic coding tools (e.g., Claude Code, Cursor, GitHub Copilot) and teaching these practices to others

• Familiarity with MQTT, AMQP, REST APIs , and enterprise integration patterns

• Relevant certifications such as AWS Certified Machine Learning or Generative AI, Azure AI Engineer Associate, or Google Professional Machine Learning Engineer

• Prior experience creating workshop collateral, reference architectures, or technical content (blogs, talks, demos) on agentic AI

What Success Looks Like

• Customers move agentic AI solutions from pilot to production and realize measurable business value, not just successful demos

• Agentic systems you deliver follow the ADLC and are reliable, secure, observable, and governed , with clear evaluation criteria and operational ownership

• Customers view you as a trusted advisor on agentic AI and event-driven architecture , and bring you into their AI strategy and architecture decisions

• Customer teams are enabled to operate and extend the solutions independently after handover

• Proactive recommendations lead to new use cases, expanded adoption of the company Agent Mesh , and broader use of the the company Platform

• Risks around data access, security, cost, and model behavior are identified early and addressed before they affect delivery or production

• Strong customer relationships contribute to renewals, expansion, and long-term partnership

• Reusable agent patterns, accelerators, and ADLC assets are created and adopted across the Professional Services organization

Why You’ll Love Working at the company

At the company, we’re all about smart people, meaningful work, and good vibes.

• Work with brilliance – Our team is packed with some of the sharpest minds in the industry.

• Balance matters – We believe work should fit into your life, not the other way around.

• Hybrid-first – Flexibility is built into how we work, so everyone feels included and empowered.

• Values-driven – We live and breathe our core values: craftsmanship, trust, courage, freedom, momentum, humility, and human experience.

• Growth mindset – Our training programs are designed to help you level up, fast.

• Customer Obsessed – We’re proud of our world-class customer lineup (we’re not shy about it).

• Keep it fun – We’re social, we keep things simple, and we know how to have a good time.

• Creative culture – We’ve got a great sense of humour and we make cool videos on topics like MITT and this (check them out!).

At the company, we are committed to a fair, inclusive, and transparent recruitment process.

To help identify candidates whose qualifications best align with the role, we use artificial intelligence (AI) tools during the initial stage of resume screening. These tools compare submitted resumes to the job description, focusing on education, experience, and skills.

Importantly, all decisions beyond this initial screening—including interviews and final hiring—are made by our human recruitment team. AI is never used to make final hiring decisions.

Let’s Talk

Not sure you meet every requirement? That’s okay — we’re more interested in your potential and passion. If this role excites you, we’d love to hear from you.

Need

accommodations during the hiring process? Just let us know — we’re here to support you.

Thanks to everyone who applies! While we wish we could connect with every candidate, only those selected to move forward will be contacted.

At the company, we believe that diversity and inclusion drive innovation and growth, both in business and in life. We strive to create an enriching and safe workplace where you can be who you are. If you want to do the best work of your career and feel supported every step of the way, we encourage you to join us!

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