Job 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. 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. Accellor is seeking a Senior AI Solutions Engineer to design and build production-grade AI solutions. What You’ll Do • Design, build, and deploy production-grade enterprise AI solutions using Glean and Python. • Configure, extend, and integrate Glean AI to create intelligent enterprise search, knowledge discovery, and AI-powered experiences. • Build LLM-powered applications using prompt engineering, model integrations, tool calling, and AI workflows. • Design and implement RAG solutions using embeddings, vector search, retrieval, knowledge grounding, and evaluation. • Connect Glean and AI applications with enterprise platforms, external APIs, databases, and knowledge sources. • Build scalable backend services, APIs, data models, connectors, and application integrations. • Develop agentic AI workflows using tools such as MCP and multi-agent patterns where appropriate. • Partner directly with business and technical stakeholders to understand use cases, translate ambiguous requirements, and design practical AI solutions. • Apply strong engineering practices around testing, security, observability, scalability, and performance. Requirements • 5+ years of professional software engineering, solutions engineering, or AI application development experience. • Hands-on experience implementing, configuring, integrating, or developing solutions with Glean AI. • Strong hands-on Python development experience. • Experience developing production applications using LLMs and generative AI. • Experience designing and implementing RAG architectures, enterprise search, vector search, embeddings, and knowledge retrieval. • Experience integrating AI solutions with APIs, databases, enterprise applications, and knowledge sources. • Understanding of agentic AI concepts, including tool calling, MCP, and multi-agent workflows. • Strong software engineering fundamentals, including APIs, testing, security, scalability, and production support. • Strong communication and problem-solving skills with the ability to work directly with business and technical stakeholders. Benefits At Accellor, we believe in equitable compensation. The salary for this position is $200,000-225,000. The actual pay will depend on your skills, experience, and qualifications. The salary range is subject to change. Speak with your recruiter about any questions.

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Must-haves

Accellor is seeking a Senior AI Solutions Engineer to design and build production-grade AI solutions.
What You’ll Do
Design, build, and deploy production-grade enterprise AI solutions using Glean and Python.
Configure, extend, and integrate Glean AI to create intelligent enterprise search, knowledge discovery, and AI-powered experiences.
Build LLM-powered applications using prompt engineering, model integrations, tool calling, and AI workflows.
Design and implement RAG solutions using embeddings, vector search, retrieval, knowledge grounding, and evaluation.
Connect Glean and AI applications with enterprise platforms, external APIs, databases, and knowledge sources.
Build scalable backend services, APIs, data models, connectors, and application integrations.
Develop agentic AI workflows using tools such as MCP and multi-agent patterns where appropriate.
Partner directly with business and technical stakeholders to understand use cases, translate ambiguous requirements, and design practical AI solutions.
Apply strong engineering practices around testing, security, observability, scalability, and performance.
5+ years of professional software engineering, solutions engineering, or AI application development experience.
Hands-on experience implementing, configuring, integrating, or developing solutions with Glean AI.
Strong hands-on Python development experience.
Experience developing production applications using LLMs and generative AI.
Experience designing and implementing RAG architectures, enterprise search, vector search, embeddings, and knowledge retrieval.
Experience integrating AI solutions with APIs, databases, enterprise applications, and knowledge sources.
Understanding of agentic AI concepts, including tool calling, MCP, and multi-agent workflows.
Strong software engineering fundamentals, including APIs, testing, security, scalability, and production support.
Strong communication and problem-solving skills with the ability to work directly with business and technical stakeholders.

Nice-to-haves

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aipythonllm

Platform: workable
Effort: medium

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