Lead AI Engineer

Accelloris an AI-native services firm purpose‑built for the post‑ChatGPT era. Free from legacy constraints, we focus on delivering measurable business outcomes through advanced AI, data, and engineering capabilities. Our mission is to operationalize AI at scale and unlock sustained enterprise value.

Our offerings span AI solutions, data services, enterprise applications, and product engineering, tailored to industry‑specific needs across healthcare, life sciences, telecom, retail, financial services, and technology. By leveraging design‑thinking and technology‑agnostic architectures, we ensure faster time‑to‑value and seamless interoperability.

With a proven track record of enabling Fortune 100 enterprises and global innovators, Accellor stands as a trusted partner for organizations seeking to harness the full potential of AI. Our vision is clear: to build intelligent, connected ecosystems that deliver measurable outcomes and redefine the future of enterprise transformation.

We are seeking a Lead AI Engineer to architect and deliver next‑generation Agentic AI solutions powering our Marketing workstream. This role will lead the design and implementation of autonomous, multi‑agent systems that drive personalization, content generation, campaign optimization, analytics, and intelligent customer engagement.

You will work at the intersection of LLMs, agent frameworks, AWS cloud‑native AI services, and marketing technology systems, building scalable production‑grade AI systems — not just prototypes.

This is a hands‑on technical leadership role for someone who understands both AI architecture and real‑world deployment at scale.

• Design and implement production‑grade agentic AI systems using frameworks such as Lang Chain, Lang Graph, and other open‑source LLM orchestration tools
• Build multi‑agent workflows with memory, tool use, reasoning chains, and autonomous decision‑making
• Develop RAG (Retrieval‑Augmented Generation) systems integrated with marketing data sources
• Implement evaluation, guardrails, observability, and continuous improvement loops

• Architect scalable AI systems using AWS services
• Deploy and manage AI agents in secure, production cloud environments
• Implement CI/CD and MLOps best practices for model lifecycle management

• Build AI‑driven solutions for campaign content generation, customer segmentation and targeting, conversational marketing agents, lead qualification agents, and performance analytics automation
• Integrate AI agents with CRM, CDP, marketing automation, and analytics platforms
• Collaborate with marketing stakeholders to translate business needs into AI‑driven workflows

• Provide technical leadership and architecture direction for AI initiatives
• Mentor engineers and establish engineering standards for AI systems
• Define best practices around prompt engineering, model selection, safety, and responsible AI
• Drive evaluation frameworks for LLM accuracy, cost optimization, and performance
• 8+ years of software engineering experience, with 3+ years in AI/LLM systems
• Proven experience building and deploying Agentic AI systems in production
• Deep hands‑on experience with Lang Chain, Lang Graph, and open‑source LLM orchestration frameworks
• Strong experience with AWS AI ecosystem, especially Bedrock and Sage Maker
• Experience building RAG systems with vector databases (Pinecone, Open Search, Weaviate, etc.)
• Strong Python engineering background
• Experience building APIs and integrating AI systems with enterprise platforms
• Experience designing scalable cloud‑native architectures

We focus on industries like High‑Tech, communication, media, healthcare, retail, and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them.

You can expand your skills by collaborating with a diverse team of highly talented people.

Accellor prioritizes work‑life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays.