Senior/Lead Applied AI Engineer

About IFS Loops
IFS Loops, an IFS company, is the first enterprise-grade AI Agent platform built for SaaS, CX, and mission-critical industries. Our AI Agents are like digital coworkers: secure, always learning, and working 24/7 to drive measurable business outcomes. As we grow, we're looking for mission-driven individuals to help us deliver the future of AI-powered operations.
At IFS Loops, we:
Lead with Curiosity: We ask questions, learn, and communicate with respect for each other.
Learn by Making: We iterate fast to deliver tangible solutions with humility.
Listen to the Loop: We use data and feedback to map our path to success and measure it with autonomy and empathy. IFS Loops is redefining how modern organizations scale, and our customers rely on us to unify their technical stack and deliver real-time, AI-powered insights and Agentic capabilities.
Summary
As a Senior/Lead Applied AI Engineer, you will architect, build and operate production-grade AI Agents and Multi-Agent systems that translate complex enterprise workflows into autonomous AI agent logic. You’ll design, configure, and deploy AI agents that streamline workflows, improve compliance, and enhance operational efficiency. The role blends domain expertise, hands-on technical skills, and applied AI development. You will also provide technical leadership across the agent delivery lifecycle, shaping solution design, driving implementation standards, and supporting production readiness in collaboration with platform and sustaining teams.
AI Agent Design & Development Translate business processes and sourcing workflows into robust, autonomous AI agent logic. Architect business requirements into multi-agent systems, defining agent boundaries, tool contracts, memory strategy, and orchestration flows. Configure and develop AI agents to automate purchasing, vendor management, and approval processes. Apply MCP (Model Context Protocol)-style tool interoperability and integration patterns to standardize agent-to-tool interactions. Develop and test agent logic using strong engineering practices, scripting and platform tools including automated testing, reviewable code changes, and versioned releases. Design and implement prompting strategies (prompt templates, system constraints, guardrails, output schemas, versioning).Collaborate with AI engineers to optimize agent performance, scalability, reliability, and cost/latency trade-offs in production.
Process Understanding & Translation Work with SMEs to map end-to-end sourcing and purchasing processes into structured agent workflows. Ensure AI agent behavior aligns with policies, business rules, and compliance standards. Maintain clear technical documentation for deployment, configuration, and ongoing sustainment including decision logs and runbooks for support teams.Identify workflow risks, edge cases, and failure modes early, and propose mitigation strategies (approvals, fallbacks, escalation paths).
Cross-functional Collaboration Partner with Implementation & Sustaining Engineering to deploy and maintain AI agents in production environments. Collaborate with Product and Platform teams to improve features and scalability. Support customers through validation, training, and feedback cycles to ensure successful adoption.Lead technical discussions with cross-functional stakeholders, drive alignment on agent behavior and success criteria, and unblock delivery.
5+ years in software engineering and/or applied AI Engineering experience with 1-2 years focused on Generative AI, Agentic AI & LLMs-based systems in production.
Exposure to one or more domains is preferred: Supply Chain, Asset Management, Procurement and FSM Experience with MCP/A2A and emerging agent interoperability standards/patterns.
Strong software development or scripting experience (Python, JavaScript, or equivalent).
Strong understanding of enterprise integrations, data flow, and automation logic.
Familiarity with AI frameworks or orchestration platforms like LangChain, LangGraph preferred.
Exposure to safety and security practices for agentic systems (guardrails, policy engines, prompt injection defenses).
Proven ability to translate ambiguous business goals into technical architectures and executable delivery plans.
Experience driving technical decisions, setting implementation standards, and mentoring or guiding other engineers.
Track record of building reusable patterns and improving engineering quality (testing, documentation, reliability, operational readiness).
Strong analytical, problem-solving, and communication skills.

Employment type
Full-time

Work arrangement
Hybrid