Job Description

Agentic AI is being touted as the most significant growth potential in AI. However, the ability to safely operationalize Agentic AI by securely bridging probabilistic AI to deterministic certainty required by enterprise operations remains the most significant missing link. This is why up to 95% of enterprise AI projects fail to reach production.

The reason is apparent.

The five decades of the deterministic computing paradigm have rendered nearly all IT systems and automation applications deterministic. This means all workflow, BPM, Low-Code, and/or even vibe coding are designed to create predefined, structured happy-path automation, posing a paradigm-mismatch challenge for coping with AI's probabilistic nature.

As a result, AI agents are often utilized as standalone bolt-ons in traditional structured process automation, which significantly limits the return on investment (ROI) of AI.

AgilePoint's industry-leading composable architecture with 30+ architected-in dynamic patterns enables structural governance for multi-model and multi-agent orchestration, as well as adaptive process orchestration.

Before the rise of Agentic AI in 2024, AgilePoint's composable platform had been adopted by mission-critical enterprises, including those in global financial services, banking, defense contractors, and more, since 2007.

AgilePoint is one of the vendors awarded by GovTech bulk tender GVT(T) 23008A.

We are looking for a self-driven, solution- and customer-oriented technical professional with the following qualifications:

Agentic AI Consultant & Application Architect —

· Bachelor's or Master's in Computer Science, Software Engineering, or related field (sometimes substituted by equivalent experience)

· Solid grounding in software architecture patterns — event-driven design, API-first/composable architecture

· Experience with enterprise integration since agentic AI has to plug into existing systems, not replace them

· Enterprise/consulting skills

Experience translating business processes into technical requirements — often coming from a BPM, RPA, or workflow automation background
Stakeholder management and the ability to sell a technical vision to non-technical executives (especially CIOs)
Change management chops, since agentic AI rollouts usually require process redesign, not just a tech swap

· AI/ML-specific experience preferred

Hands-on work with LLMs and agent frameworks
Understanding of RAG (retrieval-augmented generation), prompt engineering, and fine-tuning basics
Familiarity with the practical failure modes of probabilistic systems — hallucination, non-determinism, drift — and how to design guardrails around them (human-in-the-loop checkpoints, validation layers, structured governance)

· Enterprise-to-technical translation: Comfortable operating at the CIO/CxO level — explaining why architected-in governance beats bolted-on guardrails, and why that distinction determines whether AI reaches production

Learn more by visiting https://www.agilepoint.com

See AgilePoint platform in action:

https://youtu.be/3nsOOTrJsugsi=vVYtB2QV2sWK4kAf