Assent
SaaS sustainability
Sr.DataEngineer-AIML
Neural analysis suggests this role is
optimal for mid candidates.
“Sr. Data Engineer - AI ML at Assent. Skills: Knowledge base construction, Retrieval-augmented reasoning (RAQ/RAG), Generative AI data pipelines, Agentic AI systems, Knowledge graphs, Vectorized stores. Design, build, and optimize data pipelines for Agentic and Generative AI systems, enabling context retrieval, multi-step reasoning, and adaptive knowledge updates.. Develop and manage knowledge bases, vector stores, and graph databases to organize and retrieve information across diverse regulatory”
What You'll Achieve.
Enable Assent’s R&D toward Agentic AI systems.; Design, build, and maintain intelligent data infrastructures that supply context, memory, and reasoning capabilities to autonomous AI agents.; Connect structured and unstructured enterprise data into continuously updated knowledge graphs and vectorized stores that empower dynamic retrieval, planning, and decision-making.; Create scalable, auditable, and high-fidelity data pipelines that feed both assistive and autonomous AI functions.
Industry & Context.
What They're Looking For.
Must Have
8+ years of experience in data engineering or applied AI infrastructure, with hands-on expertise in knowledge-centric or agentic AI systems., Proven experience building retrieval-augmented generation (RAG) and retrieval-augmented reasoning/querying (RAQ) data pipelines., proficiency in Python and SQL, with experience designing large-scale data processing and orchestration workflows (Airflow, Prefect, Step Functions, or similar)., Deep familiarity with vector databases (e. g. , Weaviate, Pinecone, FAISS, Elastic Vector Search, Milvus) and graph databases (e. g. , Neo4j, AWS Neptune, ArangoDB)., Hands-on experience with embedding generation, semantic indexing, and context chunking for LLM retrieval and reasoning., Experience with agentic AI protocols and orchestration frameworks such as Model Context Protocol (MCP), LangChain Agents, Semantic Kernel, or DSPy, LlamaIndex Agents, or custom orchestration layers enabling seamless interaction between models, tools, and enterprise data sources., Knowledge of cloud data platforms (AWS preferred: S3, Glue, Lambda, ECS, Athena, Redshift) and infrastructure-as-code tools., Knowledge of data modeling, schema design, and indexing strategies for both relational and NoSQL systems., Understanding of LLM data workflows, including prompt evaluation, retrieval contexts, and fine-tuning data preparation., Be familiar with corporate security policies and follow the guidance set out by processes and procedures of Assent.
What You'll Do.
and optimize data pipelines for Agentic and Generative AI systems
enabling context retrieval
and adaptive knowledge updates.
Develop and manage knowledge bases
and graph databases to organize and retrieve information across diverse regulatory
and supplier domains.
Engineer retrieval-augmented reasoning (RAQ/RAG) pipelines
integrating embedding generation
and retrieval orchestration for LLM-driven agents.
Implement and automate workflows for ingestion of structured and unstructured content (documents
metadata) into searchable
continuously enriched data stores.
Design feedback and reinforcement loops that allow AI agents to validate
and refine their knowledge sources over time.
and traceability through schema validation
and lineage tracking within knowledge and vector systems.
Integrate monitoring and observability to measure retrieval performance
and model-data alignment for deployed agents.
and data models to ensure reproducibility
and long-term maintainability.
Stay at the forefront of AI data innovation
evaluating new technologies in graph reasoning
embedding architectures
autonomous data agents
and memory frameworks.
How You'll Work.
Team & Collaboration
Collaborate cross-functionally with AI/ML, MLOps, Data, and Product teams to define data ingestion, transformation, and retrieval strategies aligned with evolving AI agent capabilities.; Collaborate with data governance and security teams to enforce compliance, access control, and Responsible AI data handling standards.
Full Job Description
Assent is the leading solution for supply chain sustainability tailored for the world’s top-tier, sustainability-driven manufacturers. Hidden risks riddle supply chains, many of which weren't built with sustainability in mind. That's where we step in. With insights from experts, Assent is the tool manufacturers trust for comprehensive sustainability. We are proud to announce that Assent has crossed the US$100M ARR milestone, granting us Centaur Status. This accomplishment, reached just 8 years following our Series A, makes us the first and only Certified B Corporation in North America's SaaS sustainability industry to celebrate this milestone. Our journey from $5 million to US$100M ARR in just eight years has been marked by significant growth and achievements. With our $350 million US funding led by Vista Equity Partners, we're poised for even greater expansion and are on the lookout for outstanding team members to join our mission. Hybrid Work Model At Assent, we proudly embrace a remote-first work model, valuing the flexibility and autonomy it provides our team. We also acknowledge the intangible benefits of occasional in-person workdays. For team members situated within 50 kms/31 miles of our five global offices in Ottawa, Eldoret, Penang, Columbus, Pune and Amsterdam, you can expect to come into the office 1-3 days a week. Similarly, those near our co-working spaces in Nairobi and Toronto are encouraged to work onsite once a month. We are seeking a Senior Data Engineer, AI/ML with deep expertise in knowledge base construction, retrieval-augmented reasoning (RAQ/RAG), and Generative AI data pipelines to help enable Assent’s R&D toward Agentic AI systems. In this role, you will design, build, and maintain intelligent data infrastructures that supply context, memory, and reasoning capabilities to autonomous AI agents. Your work will connect structured and unstructured enterprise data into continuously updated knowledge graphs and vectorized stores that empower dyna
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