Seekr Technologies

Business Development Rep

• Drive pipeline: run outbound sequences, prospect target accounts, hold discovery conversations, and drive sales-accepted opportunities. The motion gets proven by you doing it, not by you managing someone else doing it.
• Build the systems the motion runs on: outbound scripts and talk tracks, sequencing strategy, persona definitions and account segments, inbound qualification criteria, discovery framework, and sales engagement tooling configuration. Build them by running, testing, and optimizing.
• Own outbound sequencing strategy. Work with Technical Product Marketing to ensure the messaging in outbound matches the master framework. Work with Demand Generation on integration into broader campaigns.
• Own inbound qualification in partnership with MOPs and Demand Gen. Define the criteria, manage the SLA on response time, and own the activation.
• Partner with Marketing Operations on routing, sequencing and tooling, and reporting on BDR-sourced pipeline.
• Partner with sales leadership on account prioritization, lead acceptance criteria, and the handoff motion.
• Run the feedback loop. BDR conversations are a free intelligence stream on objections, language, and competitive positioning. Capture it and route it back to Marketing.
• Hit pipeline targets. BDR performance is measured in sales-accepted opportunities and pipeline creation, not how many cold calls you made.
• Build and operate AI-accelerated workflows across the BDR motion - prospect research, account intelligence, sequence personalization, conversation analysis, objection-handling pattern detection. AI accelerates the rep; AI does not replace the rep.

BDR Manager

AI Engineer

• Design and build explainability capabilities that help users understand why a model or agent produced a given output and what training data, retrieved documents, tools, agent interactions, or internal model mechanisms influenced that result.
• Build evaluation frameworks for explanation quality across dimensions such as faithfulness, sufficiency, consistency, and plausibility of explanations.
• Design and build contestability capabilities that enable users to challenge AI outputs, capture corrective feedback, and turn contested results into data that improves systems over time.
• Work on adjacent high-impact areas such as hallucination detection and mitigation, and continual-learning agents that can learn from explainability signals and contested outputs.
• Translate and synthesize promising ideas from current literature into prototypes, and translate validated prototypes into production-grade features.
• Contribute across the AI system lifecycle where needed, including model development, inference, deployment, and monitoring.
• Partner with product, design, and customer-facing teams to make explainability useful in real workflows, not just technically interesting.
• Use AI coding assistants effectively and reliably as part of a modern engineering workflow while maintaining strong judgment and code quality.

Senior AI Engineer / Research Scientist, Explainable AI

Engineer

• Operationalizing AI PoCs by transforming demos and prototypes into robust, production-grade AI systems.
• Designing and deploying data pipelines and retrieval frameworks that prepare enterprise data for LLM training, fine-tuning, and RAG-based applications.
• Fine-tuning, evaluating, and deploying large language models and agentic workflows, ensuring outputs remain grounded, explainable, and compliant.
• Integrating SeekrFlow AI agents with customer environments, containerizing and orchestrating them across cloud, hybrid, and on-prem deployments (AWS, Azure, GCP, private cloud).
• Embedding with client engineering teams to debug model behavior, optimize inference performance, and implement monitoring/guardrails for safe operation.
• Codifying best practices into reusable playbooks, evaluation frameworks, and deployment accelerators that scale AI adoption across industries.

BDR Manager

Senior AI Engineer / Research Scientist, Explainable AI

Forward Deployed Engineer