Lead AI Engineer at Accellor

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

14 May, 26

Salary

0.0

Posted On

13 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Agentic AI Architecture, LangChain, LangGraph, RAG, AWS AI Services, Bedrock, SageMaker, Vector Databases, Python Engineering, CI/CD, MLOps, API Development, Cloud-Native Architectures, Prompt Engineering, LLM Orchestration, Technical Leadership

Industry

IT Services and IT Consulting

Description

Accellor is 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. Responsibilities: Agentic AI Architecture & Development Design and implement production-grade agentic AI systems using frameworks such as LangChain, LangGraph, 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 AWS AI & Cloud Engineering 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 Marketing AI Workstream Enablement Build AI-driven solutions for: Campaign content generation Customer segmentation and targeting Conversational marketing agents Lead qualification agents 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 Leadership & Governance 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: LangChain LangGraph Open-source LLM orchestration frameworks Strong experience with AWS AI ecosystem, especially Bedrock and SageMaker Experience building RAG systems with vector databases (Pinecone, OpenSearch, Weaviate, etc.) Strong Python engineering background Experience building APIs and integrating AI systems with enterprise platforms Experience designing scalable cloud-native architectures Exciting Projects: 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. Collaborative Environment: You can expand your skills by collaborating with a diverse team of highly talented people. Work-Life Balance: Accellor prioritizes work-life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays. Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training, Stress Management program, professional certifications, and technical and soft skill training. Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, Personal Accident Insurance, Periodic health awareness program, extended maternity leave, annual performance bonuses, and referral bonuses. Disclaimer Accellor is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic

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Responsibilities

This role involves leading the design and implementation of autonomous, multi-agent systems for the Marketing workstream, focusing on personalization, content generation, and intelligent customer engagement. Responsibilities include architecting production-grade agentic AI systems using frameworks like LangChain and developing RAG systems integrated with marketing data sources.