About the Role & Team

IDC is building the next generation of AI-powered intelligence platforms that transform how technology decisions get made. Our platform re-imagines the way decision-makers discover and interact with trusted research and data, and is foundational to IDC's future.  We are looking for an AI/Agent Engineer to join the Memory / Living Intel Pod, focused on memory extraction, compactification, and context assembly. You will build the LLM-powered capabilities that allow the platform to remember users across sessions: summarizing conversations, extracting durable facts and preferences, and assembling relevant context so that agents can deliver personalized, informed responses.  This is an LLM application engineering role. You will work within multi-agent pipelines, designing the extraction and retrieval logic that turns conversation history into structured, usable memory. Your work directly shapes how intelligent and personalized the platform feels to every user. 

What You’ll Do

• Build specialized agents within multi-agent pipelines designed for handling complex research problems, developing durable outputs, and taking action in external systems on the user's behalf
• Build LLM-based memory capabilities: conversation summarization, cross-session context retrieval, and persistent user preference extraction
• Design and implement extraction pipelines that identify durable facts and preferences from conversations
• Build context assembly systems that provide agents with relevant user history and memory
• Instrument pipelines for observability, tracing, and quality monitoring
• Collaborate with evaluation engineers on quality measurement and improvement

What You Bring

• 3+ years of experience building production Python systems
• Experience with LLM applications: agent orchestration, prompt engineering, RAG, or similar
• Hands-on experience with agent frameworks (LangGraph, LangChain, CrewAI, AutoGen, or similar)
• Understanding of LLM reasoning patterns and common failure modes
• Proficiency with modern Python web frameworks
• Comfort working in a fast-moving team where priorities evolve

Preferred Qualifications: 

• Experience with semantic search, embeddings, and vector databases (e.g., Snowflake Cortex, Pinecone, Weaviate)
• Familiarity with LLM observability tools
• Background in NLP, text summarization, or information extraction
• Experience building systems that maintain user context or state over time
• Familiarity with enterprise data systems (analytics APIs, data warehouses, SQL)

Why This Role Stands Out
At IDC, your work helps shape how the world understands technology and where it goes next. You collaborate with curious, high-caliber colleagues who value rigor, integrity, and shared success. As the premier global provider of trusted technology intelligence, IDC equips business and technology leaders with the evidence they need to make confident decisions. Our insights inform strategy, investment, and innovation across industries and regions.

Recognized by IIAR as Analyst Firm of the Year for five consecutive years, IDC sets the standard for credibility and impact. With more than 1,000 analysts worldwide and a truly global perspective, we combine deep expertise with practical relevance. Here, your ideas matter, your voice is heard, and your contributions provide the insights leaders rely on every day. It is meaningful work, backed by a culture that supports growth, collaboration, and long-term career development with a globally respected brand.

What We Offer

• Hybrid/remote work model (about 1-2 days in the office per month).

• A position in a highly professional and globally respected market research and advisory firm, where initiative leading to results is rewarded.

• Individualized Culture: An environment where you can explore new areas outside your specialty and stay engaged with work you enjoy.

Equal Opportunity Employer

IDC is committed to providing equal employment opportunities for all qualified persons. Employment eligibility verification required. We participate in E-Verify. 

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