7+ years in applied ML/AI or realtime distributed systems; 3+ years leading production LLM/voice solutions.
Experience in building realtime voice agents with measurable business impact.
Hands-on fine-tuning expertise in data curation and SFT.
Production RAG experience with strong observability for conversational applications.
Strong programming skills in Python and PyTorch; familiarity with TypeScript is a plus.
Bachelor's degree in Computer Science required; Master's in CS (AI focus) preferred.
Experience with governed data/ML platforms and secure deployment patterns.
Responsibilities
Architect low-latency streaming pipelines and telephony integrations for enhanced user experience.
Design reference architectures and SDKs for AI technologies, driving team adoption through comprehensive documentation.
Build automated evaluation pipelines and standards to ensure quality before deployment.
Define evaluation criteria for Conversational AI systems and implement monitoring tools for performance assessment.
Collaborate with Data/Platform teams for secure and governed deployment of AI solutions.
Lead vendor assessments, offering insights on build vs. buy strategies based on economic models.
Mentor and review work for engineers and data scientists, fostering knowledge sharing across teams.
Benefits
Comprehensive health and welfare benefits, including medical, dental, vision, and flexible spending accounts.
Generous paid leave policies including holidays, annual PTO, and various forms of disability leave.
Retirement benefits featuring a savings plan with company contributions.
Wellbeing programs and work/life resources, including employee assistance services.
Full Job Description
About the Role
We are hiring a hands-on AI Engineering leader to design and scale TRANZACT's next-generation Conversational & Composable AI stack across three pillars: Voice AI, Agentic AI, and AI-driven Analytics. You will own systems-level architecture and delivery-from low-latency speech and telephony to agentic orchestration and governed analytics-turning unique data assets into durable business outcomes. This role combines strategic ownership with sleeves-rolled-up execution.
What You'll Own (Systems-Level Outcomes)
Define and evolve the end-to-end Conversational AI platform: realtime ASR agentic reasoning TTS with sub-second turn-taking and production-grade reliability.
Establish scalable multi-agent patterns (task routing, tool use, memory, human-in-the-loop) and standard SDKs/templates to accelerate team adoption.
Stand up enterprise-grade Conversational RAG: hybrid retrieval, grounding/citation, freshness, and streaming context for voice/chat.
Implement Responsible AI controls, observability, and governance (catalogs, lineage, model registry, policy enforcement) across the stack.
Uplift the broader Engineering org by sharing reusable components, golden paths, and best practices; reduce vendor dependency via self-service capabilities.
Serve as Lead Engineer/Producer for at least one critical initiative per quarter, driving requirements architecture implementation launch post-launch learning.
Key Responsibilities
Architect low-latency streaming pipelines and telephony/queue integrations (SIP/IVR/contact center) to support overflow, warm transfer, and compliant prompts.
Design reference architectures and SDKs for Voice AI, Agent Assist, QA & Monitoring, and Conversational Analytics; drive adoption via docs and enablement.
Build fine-tuning pipelines (data curation, SFT, preference/reward optimization, safety tuning) and automated eval gates prior to promotion.
Define eval suites (faithfulness, answer relevance, context recall, ASR WER, latency budgets) and instrument tracing/attribution/redaction across the retrieval/generation chain.
Partner with Data/Platform for governed deployment: role-based access, audit trails, change capture, freshness SLAs, and model/asset lifecycle management.
Lead vendor benchmarking and make build/buy/insource recommendations aligned to unit economics, reliability, and IP strategy.
Mentor engineers/data scientists; review designs, prompts, datasets, and PRs; host tech talks and share reusable components across teams.
Success Profile (6-12 Months)
Conversational AI platform reliably supports key production use cases with clear SLOs and runbooks.
Reusable SDKs/templates and "golden paths" enable faster delivery across teams; internal adoption measurably increases.
Enterprise Conversational RAG delivers grounded answers within voice turn-taking budgets, with healthy eval & monitoring signals.
Responsible AI controls and governance are standardized and auditable across Voice/Agentic/Analytics workloads.
A critical initiative is led to launch with documented impact and a retrospective feeding the platform roadmap.
Minimum Qualifications
7+ years in applied ML/AI or realtime distributed systems; 3+ years leading production LLM/voice solutions.
Proven experience building realtime voice agents (WebRTC-class streaming or equivalent) with measurable business impact.
Hands-on fine-tuning experience (parameter-efficient and, when needed, full-parameter): data curation, SFT, preference/reward optimization, safety tuning, and evals.
Production RAG for conversational use cases (hybrid retrieval, reranking, caching, grounding/citation) with strong observability.
Strong engineering in Python and PyTorch; exposure to TypeScript or similar is a plus.
Bachelor's degree in Computer Science required; Master's in CS (AI focus) preferred.
Experience with governed data/ML platforms (catalog, registry, lineage) and secure deployment patterns.
Track record of mentoring and uplifting teams; effective communicator with stakeholders across technical and non-technical domains.
Streaming RAG for Voice AI (incremental retrieval, early-token generation/TTFB optimization, barge-in-friendly generation).
Telephony/contact-center systems and marketing analytics experience.
How We Work
Composable AI first: best-in-class components while protecting proprietary data/process IP.
Agile and iterative: prove value quickly, then scale with governance and reliability.
Responsible by default: industry frameworks, content controls, lineage, permissions, and continuous evaluation.
Compensation and Benefits
Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that base salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation.
Compensation
The base salary compensation range being offered for this role is $250, 000 USD per year.
This role is also eligible to participate in the annual bonus program.
Company Benefits
TRANZACT provides a competitive benefit package which includes the following (eligibility requirements apply):
Health and Welfare Benefits: Medical (including prescription coverage), Dental, Vision, Health Savings Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program)
Leave Benefits: Paid Holidays, Annual Paid Time Off (includes state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave)
Retirement Benefits: Savings Plan with annual nonelective company contribution.
