Agentic Engineer

Job not on LinkedIn

🕒 September 1

🇵🇪 Peru – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Livefront

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2001

💼 Consulting

🤖 Artificial Intelligence

🤝 B2B

💰 Private equity on 2023-10

Consulting • Artificial Intelligence • B2B

Livefront is a digital product and engineering consultancy that builds AI-first products, platforms, and intelligent agents for enterprise clients. The firm combines strategy, product design, AI & automation, digital engineering, and data & analytics in a co-creative model (called MESH) to accelerate digital transformation and ship customer-facing software from discovery through scale. Livefront highlights work across healthcare, retail, automotive, and large enterprises—delivering AI companions, revenue-optimization agents, conversational/LLM integrations, platform engineering, and modern data pipelines to improve product outcomes and operational efficiency. The company positions itself as a partner-first, B2B services provider focused on measurable business impact.

📋 Description

• Work directly with clients to understand complex business problems and translate them into scalable, production-ready agentic AI solutions • Design and implement multi-step agent systems, including orchestration, tool and function calling, task decomposition, and multi-agent coordination when appropriate • Build integrations between agents and enterprise systems using APIs as tools, MCP servers, and structured tool contracts • Design evaluation frameworks, guardrails, grounding and citation checks, and human-in-the-loop workflows • Instrument agent systems for traceability and observability, including actions, model behavior, token and cost usage, latency, and system performance • Design and maintain state and memory across long-running workflows • Implement model routing, retries, idempotency, and other reliability patterns • Build and deploy AI solutions using Azure or AWS cloud platforms and services • Apply software engineering practices using Python, Java, APIs, containers, source control, automated testing, and CI/CD • Collaborate with client engineering and security teams through architecture reviews, threat modeling, security reviews, audits, and enterprise delivery requirements • Evaluate when agentic architectures are appropriate versus deterministic pipelines, traditional machine learning, or other approaches • Turn successful client-engagement approaches into reusable Zeal patterns and solutions • Build trust with clients and internal teams through communication, technical judgment, problem-solving, and execution

🎯 Requirements

• Strong software engineering foundation • Hands-on experience designing and shipping production agentic AI systems • Experience with tool and function calling, multi-step workflows, orchestration, task decomposition, or multi-agent architectures • Experience evaluating agent behavior and measuring system failures • Experience building evaluation harnesses, guardrails, grounding checks, human-in-the-loop controls, and error mitigation mechanisms • Deep hands-on experience with either Azure or AWS and related AI and infrastructure services • Strong proficiency in Python or Java • Proficiency in API design, containers, automated testing, source control, and CI/CD • Sufficient machine learning knowledge to determine when traditional ML or deterministic approaches are more appropriate than an LLM • Experience delivering software within large organizations • Experience with role-based access, data isolation, security reviews, compliance, change control, and production governance • Experience with agent traceability, state and memory management, model routing, latency and cost visibility, retries, and idempotency • Excellent verbal and written communication skills • Strong technical judgment and problem-solving ability • Keen interest in consulting • Experience with MCP, emerging tool-interoperability standards, RAGAS, fine-tuning, model distillation or optimization, and highly regulated industries is helpful but not required

🏖️ Benefits

• Values-driven work environment grounded in kindness, generosity, and integrity • Variety and growth from consulting for Fortune 1000 companies across industries and technical stacks • Projects with outsized impact and reach • Human review of every application • Take-home exercise completion window of up to one week