microTECH Global is a recruitment agency specializing in permanent and contract talent for the electronics, micro-electronics, semiconductor, automotive, data science, and AI sectors. They build…
microTECH Global is a recruitment agency specializing in permanent and contract talent for the electronics, micro-electronics, semiconductor, automotive, data science, and AI sectors. They build…
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Hands-on experience across multiple agentic AI projects, ideally spanning both industrial and academic environments. Should be comfortable working at the intersection of large language models, symbolic reasoning, knowledge representation, workflow orchestration, evaluation, and full-stack (web) product development.
This is a role for someone who can move from research concepts to working systems: designing agent architectures, implementing reasoning workflows, testing reliability, building user-facing interfaces, and ensuring that agentic behaviour is interpretable, controllable, and robust.
Key responsibilitie
sDesign and implement real-world agentic AI systems using modern agent frameworks and orchestration tools
.Develop agentic workflows that go beyond chat, including complex analytical pipelines, multi-step research workflows, tool-using agents, knowledge-grounded agents, and structured decision-support systems
.Work with knowledge-based AI architectures, including retrieval-augmented generation, knowledge graphs, symbolic rules, structured domain models, ontologies, and hybrid reasoning systems
.Develop and apply mechanisms for controlling inference, including planning constraints, reasoning policies, guardrails, validation layers, tool-use control, and human-in-the-loop checkpoints
.Explore and implement neuro-symbolic approaches for agentic reasoning, combining LLM-based reasoning with symbolic, rule-based, graph-based, or formally structured methods
.Build transparent AI methods that make agent behaviour traceable, explainable, testable, and auditable
.Create evaluation and testing frameworks for agentic systems, including benchmark tasks, regression tests, failure-mode analysis, trace inspection, robustness testing, and task-level performance measurement
.Develop full-stack prototypes and production applications, integrating backend services, APIs, databases, frontend interfaces, model providers, and orchestration layers
.Collaborate with researchers, engineers, product teams, and domain experts to translate ambiguous real-world problems into reliable agentic workflows
.Stay current with developments in agentic AI, reasoning systems, LLM orchestration, AI evaluation, and applied neuro-symbolic method
**s
Required experien**
ceMust have neuro symbolic reasoning experienc
e.Strong multi-project experience developing real-world AI agents or agentic workflow
**nt
Technical Ski**
llsStrong Python engineering skil
**use
Qualifications and Portf**
olioMature open-source contributions AND
/OR.Portfolio projects related to agentic AI, LLM systems, knowledge-based AI, neuro-symbolic reason
ing.Experience building AI systems in domains such as scientific analysis, enterprise knowledge management, decision support, research automation, legal/financial/technical analysis, or complex operational workfl
ows.Experience with production-grade AI system design, including observability, monitoring, testing, security, latency, cost control, and reliabil
ity.Familiarity with human-in-the-loop systems, provenance tracking, workflow auditability, or regulated environme
nts.Experience integrating LLMs with external tools, APIs, databases, code execution environments, or analytical engi
nes.Desirable: publications (at main NLP/ML/AI conferen
ces)
s.Demonstrated focus on agentic reasoning, including planning, decomposition, tool use, multi-step inference, workflow execution, or autonomous task completio
n.Experience in either industrial AI development, academic research, or ideally bot
h.Hands-on exposure to knowledge-based agentic systems, such as agents grounded in knowledge graphs, structured documents, domain rules, ontologies, databases, or retrieval system
s.Experience with methods for controlling reasoning or inference, such as guardrails, constrained planning, validation layers, policy-based tool use, symbolic checks, or deterministic workflow component
s.Familiarity with neuro-symbolic AI concepts or hybrid reasoning architecture
s.Experience designing transparent, inspectable, or explainable AI method
s.Practical experience with agentic reasoning evaluation, testing, benchmarking, observability, or failure analysi
s.Full-stack web development experience, including backend APIs and frontend application developme
ls.Experience with modern LLM and agentic AI frameworks, especial
ly:LangCh
ainLangGr
aphOpenAI SDK / OpenAI Agents
SDKRetrieval-augmented generation syst
emsTool/function call
ingMulti-agent or multi-step workflow orchestrat
ionAgent evaluation and tracing to
olsExperience with backend development, APIs, databases, and cloud or deployment environmen
ts.Experience with frontend technologies such as React, Next.js, TypeScript, or similar framewor
ks.Familiarity with vector databases, graph databases, semantic search, structured data pipelines, or knowledge graph tooli
ng.Someone who thinks beyond prompt engineering. Should be experienced in the architecture of reasoning systems: how agents decide what to do, how inference is constrained, how knowledge is represented, how workflows are verified, and how complex AI systems can be made reliable enough for real-world
