Senior Software Engineer

Role Overview

• Embed with marketing SMEs across campaigns, property marketing, content production, social, ABM, and performance intelligence to design and ship agents that do real work in their day-to-day.
• Build, deploy, and operate production marketing AI agents that reason over regional context, brand guidelines, and intent data — and invoke tools to draft content, configure campaigns, monitor performance, and recommend optimizations.
• Design and grow the Marketing Domain Skills Library — composable LLM workflows (drafting, scoring, classification, brand-voice tuning) extracted from live agent work as reusable primitives that multiple agents can call.
• Build integrations against marketing systems (CMS, DAM, CRM, marketing automation, ad platforms, analytics) — directly when needed to unblock a pilot, and through Marketing MCP servers built by that platform team once those exist.
• Translate integration and capability gaps you hit during pilots into clear, prioritized requirements for the platform team, so the platform layer evolves to meet real agent needs rather than speculative ones.
• Own reliability, observability, evaluation, and cost efficiency of LLM-powered workflows in production — including brand-voice checks, factual grounding against property and client data, regression suites, and offline benchmarks wired into CI/CD.
• Design multi-agent orchestration patterns: how the Campaigns agent coordinates with Social, ABM, Content, Property, and Performance Intelligence; where to compose vs. where to keep boundaries; how escalations and handoffs flow.
• Set the bar for the agent pod: define the playbook for going from SME conversation to working pilot to deployed prod agent, and raise the technical quality of what the team ships.
• Represent MarTech Engineering externally — to JLL leadership, to customers, and in the broader engineering community — as a credible voice on building agents that actually work in production.
• Publish what you learn — internal write-ups, engineering blog posts, and conference talks. Forward deployed agent work surfaces novel problems and solutions every week, and externalizing them sharpens the team's thinking, raises our hiring bar, and contributes back to the broader agent engineering community.
• Stay at the frontier of agent engineering and bring the best ideas back to the team, continuously raising the bar on quality, performance, and architecture at scale.
• Drive innovation with a willingness to experiment and to boldly confront problems of immense complexity and scope.

Requirements

• You have a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent work experience
• You are proficient in English, both written and verbal, sufficient for success in a remote and largely asynchronous work environment
• You have 5+ years of software engineering experience working in production systems, including significant time integrating against enterprise APIs (CRMs, CMSes, DAMs, ad platforms, marketing automation tools, analytics)
• You have hands-on experience with modern LLM APIs across providers — including prompt engineering, tool use / function calling, structured outputs, and context engineering — and you've worked with enough of them to know that the underlying patterns transfer even as the specific APIs evolve
• You have experience designing agent systems: multi-step reasoning, tool orchestration, memory, error recovery, and human-in-the-loop escalation paths
• You've worked through the hard parts of agent engineering firsthand — hallucination grounding, tool reliability and silent failures, evals that actually predict real-world behavior (and the gap when they don't), cost and latency tradeoffs, prompt drift, and the difference between 'works in a demo' and 'still works on day 30.'
• You can talk concretely about what you've tried, what's broken on you, and what you've learned. We care more about depth of engagement with these problems than years logged
• You have experience building RAG systems — embeddings, vector stores, retrieval optimization, and grounding — and a strong intuition for when retrieval is the right answer vs. when a tool call, fine-tune, or schema change is the better lever
• You've deployed LLM-powered services or agents to production cloud environments and understand the operational reality — auth, networking, secrets, observability, rollback, cost monitoring — beyond the demo-day setup.
• You're energized by embedding directly with non-technical domain experts, can translate vague problem statements into shippable scope, and have the patience to learn an unfamiliar domain (marketing, in this case) deeply enough to anticipate where agents will fail
• You have a pragmatic bias for shipping — you can tell when a brittle workaround is the right call to unblock a pilot and when something deserves to be built right the first time
• You translate fluently between technical levels — from explaining agent failure modes to a non-technical marketing SME, to briefing leadership on architectural tradeoffs without dumbing them down, to going deep on protocol details with platform engineers, often within the same day. This skill weighs as heavily for us as your technical depth
• You have strong analytical and interpersonal skills, with a proven ability to thrive and collaborate in dynamic, product-focused, distributed teams
• You embrace a proactive approach to problem-solving and a willingness to acquire new skills and knowledge as needed to achieve results
• You're confident taking ownership of projects from start to finish and enjoy turning nebulous ideas into reality.
• You make your coworkers feel included in every interaction.

Tech Stack

• Cloud

Benefits

• 401(k) plan with matching company contributions
• Comprehensive Medical, Dental & Vision Care
• Paid parental leave at 100% of salary
• Paid Time Off and Company Holidays
• Early access to earned wages through Daily Pay