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Our client, an early-stage AI Startup, is hiring a Lead Product Engineer to join their team in New York. The successful candidate will develop production systems across conversational AI, real-time voice, intelligent retrieval and technician-facing applications, as well as own solutions from understanding operational challenges through to deployment and continuous improvement.


Responsibilities

• Build platform functionality for customer calls, diagnostics, work order management and technician dispatch.

• Develop real-time conversational agents supporting speech-to-speech interactions with technicians over voice and video.

• Deploy AI agents that engage in customer conversations across multiple channels and respond with relevant actions.

• Create and maintain production APIs and backend services supporting the field service platform.

• Build diagnostic retrieval systems using graph databases, vector search and Model Context Protocol (MCP).

• Develop dashboards and internal tools that help customers and colleagues monitor platform activity.

• Create technician-facing interfaces that provide clear, accessible diagnostic guidance in the field.

• Collaborate directly with customers and the founding team to identify challenges, ship solutions and improve features through practical feedback.

Skillset

• A track record of delivering LLMs or AI agents into production environments.

• Strong coding skills in TypeScript and Python.

• The ability to turn operational requirements into dependable, production-ready software.

• An independent approach, with confidence owning development from initial concept through to release.

• A proactive mindset and the flexibility to deliver quickly as priorities change.

• A focus on customer outcomes and improving day-to-day operations for technicians and service teams.

Benefits

• Salary: $180k - $210k.

Our client, an early-stage AI Startup, is hiring a Product Engineer to join their team in New York. The successful candidate will collaborate with the founders, engineering team and customers, owning features from understanding operational needs through to development, rollout and continuous improvement.


Responsibilities

• Build software workflows supporting customer calls, diagnostics, work orders, scheduling, dispatch, parts management and technician activities.

• Develop and launch AI agents and automation for voice, messaging and day-to-day operations.

• Design and maintain APIs, data models, integrations, dashboards and internal applications for production use.

• Engage directly with customers to identify challenges and turn their requirements into effective software.

• Take ownership of features from initial discovery through development, deployment, measurement and refinement.

• Improve platform reliability, monitoring and observability as demand increases.

• Partner with the founders and engineering team to define and deliver product enhancements.

Skillset

• Minimum of 2 years' professional experience in software engineering.

• Strong coding skills in TypeScript, with the ability to work confidently across frontend and backend development.

• Proven experience building and releasing software used in production.

• An independent, proactive approach, with the ability to own delivery and work at startup pace.

• A focus on solving customer problems and delivering measurable results.

• The flexibility to work across different technologies and respond to changing priorities.

• Experience bringing LLMs or AI agents into production is desirable.

• Knowledge of React, Python, real-time systems, voice technologies, mobile development, graph databases or external integrations is a plus.

Benefits

• Salary: $160k - $210k.

Our client, an early-stage AI Software company, is hiring a Senior AI /Machine Learning Platform Engineer to join their team in New York City. The successful candidate will develop the models and infrastructure powering diagnostics and customer experience, building shared AI capabilities across voice, chat and other agent workflows while taking ownership from data processing and model development through to deployment and continuous improvement.


Responsibilities

• Develop and operate machine learning infrastructure supporting search, retrieval, indexing, training, evaluation, inference and model deployment.

• Build and refine models for diagnostics, fault prediction, parts selection, ranking, information extraction and customer-support automation.

• Develop shared capabilities for voice and chat agents, covering context, memory, knowledge retrieval, tools, policies and continuity across channels.

• Create data and feedback pipelines drawing on service histories, technical documentation, equipment data, conversations, images and repair results.

• Maintain reliable distributed services, data pipelines, search systems and live inference through performance monitoring, capacity planning and failure recovery.

• Design evaluation frameworks that link model accuracy and retrieval quality to customer experience and repair outcomes.

• Turn conversation data, agent activity and human feedback into ongoing improvements to models and agent performance.

• Strengthen engineering workflows through automated testing, CI/CD, observability, reusable infrastructure and controls for AI-generated code.

• Collaborate with product engineers and domain experts to bring fast, explainable and dependable AI features into production.

• Make practical architecture decisions around internal development, third-party solutions, compute, storage, model providers and open-source tools.

Skillset

• At least 5 years' professional experience in software or machine learning engineering, including delivery of production systems.

• Strong coding skills in Python and TypeScript, with confidence working across models, backend systems, data platforms and cloud infrastructure.

• Sound knowledge of modern search and ML systems, including retrieval, indexing, evaluation, deployment and the challenges of models running in production.

• A strong understanding of distributed systems, performance tuning, reliability, observability and infrastructure costs.

• Experience applying AI development tools to increase productivity while maintaining engineering standards.

• The flexibility to move between research, infrastructure and product development as priorities evolve.

• An interest in creating reusable AI capabilities across diagnostics, customer support and multiple communication channels.

• A proactive approach, strong ownership and a focus on delivering measurable value to customers.

• Experience with ranking, recommendation engines, vector or graph search, multimodal models or real-time inference is desirable.

• Familiarity with ML platforms, evaluation frameworks, developer tools, GPUs, inference optimization, infrastructure as code or incident response would be an advantage.

Benefits

• Salary: $210k.

• Equity.

Our client, an early-stage AI Startup, is hiring an Agent Platform Engineer to join their team in New York City. The successful candidate will lead the development of production voice agents, create reliable, natural customer interactions and build shared tools, memory and infrastructure to support agents across the wider platform.


Responsibilities

• Develop and maintain production voice agents that handle inbound and outbound customer interactions.

• Refine conversational performance, including instruction adherence, turn-taking, interruptions, pacing, pronunciation and audio quality.

• Optimize response times across telephony, speech recognition, model processing, tool execution and speech generation while preserving accuracy and reliability.

• Build and manage infrastructure for call routing, queues, transfers, recordings, webhooks and failover.

• Create reusable agent capabilities for shared context, instructions, tools, memory, policies, identity and action execution.

• Connect agents with scheduling, diagnostic, CRM and operational platforms, ensuring reliable handling of retries, partial failures and ongoing workflows.

• Develop automated evaluations, simulations and regression tests to assess task completion, policy compliance, latency, audio quality and escalation to human teams.

• Establish monitoring and diagnostics using conversation traces, transcripts, audio events, failure analysis and alerts.

• Work closely with product and customer teams to assess real conversations, identify issues and implement improvements.

• Help define the architecture and development roadmap for the company's unified agent platform.

Skillset

• At least 2 years of experience in professional software engineering.

• A track record of building and deploying backend, real-time, telephony or conversational systems in production.

• Strong coding ability in TypeScript or Python.

• Sound knowledge of asynchronous processing, streaming, distributed systems and observability.

• The ability to balance low latency with reliable execution, instruction adherence and natural conversation.

• Confident debugging skills across application code, model responses, audio pipelines and customer configurations.

• An interest in developing reusable agent functionality that works across different channels.

• A proactive mindset, clear communication skills and the ability to take ownership in a fast-paced startup.

• Experience with Twilio, SIP or contact-centre infrastructure is desirable.

• Familiarity with LLM agents, streaming speech recognition, text-to-speech, real-time model APIs, evaluation frameworks or human handoff workflows.

Benefits

• Salary: $160k - $210k.

Our client, an early-stage AI Startup, is hiring a Forward Deployed Analyst to join their team in New York City. The successful candidate will manage the full customer journey, from technical demonstrations and implementation to adoption, retention and account growth, working closely with product and engineering teams to embed the platform into each customer's operations.


Responsibilities

• Develop customised demos, prototypes and proofs of concept that support sales and show the platform's value.

• Run technical discovery sessions to assess customer needs and define deployment requirements.

• Manage onboarding from contract signing through product configuration, integration and launch.

• Configure the platform around each customer's workflows, dispatch operations and business requirements.

• Help customers adopt the platform through practical training, regular engagement and ongoing support.

• Track account performance, manage escalations and address potential retention risks early.

• Use customer data to demonstrate ROI and uncover opportunities to grow existing accounts.

• Troubleshoot technical problems, document bugs clearly and work with engineering to resolve them.

• Turn customer insights and feedback into recommendations for product improvements.

• Create repeatable onboarding, training and customer success processes to support future growth.

Skillset

• Previous experience in solutions engineering, technical customer success or a comparable customer-facing technical position.

• Proven ability to manage customer relationships from initial demonstrations through implementation and ongoing adoption.

• Experience developing technical demos or proofs of concept that help secure new business.

• Strong technical understanding, with the ability to read code, use APIs and assess system architecture.

• Experience delivering enterprise implementations and establishing processes from the ground up.

• Clear, confident communication skills across technical and business audiences.

• A proactive, structured approach to solving problems, maintaining documentation and following up with customers.

• Commercial judgement and the ability to link platform usage to measurable customer value.

• Ability to thrive in a fast-paced startup, working independently and taking responsibility for results.

• Ambition to establish a new function, build a team and progress into a leadership role.

Benefits

• Salary: $160k - $210k.

Our client, a leading financial services organization, is hiring a Senior ServiceNow Architect to join their team in Georgia. The successful candidate will define the ServiceNow platform's architecture and roadmap, oversee solution design and ensure delivery aligns with business objectives and enterprise standards.


Responsibilities

• Shape the ServiceNow platform architecture and roadmap to meet evolving business priorities.

• Design solutions across ITSM, ITOM, HRSD, CSM, ITAM, SAM, GRC and SecOps, incorporating integrations, AI and DevOps capabilities.

• Set architectural standards, design principles and governance processes to ensure consistent implementation.

• Provide technical direction on security, data integrity, scalability, resilience and platform upgrades.

• Collaborate with architects, platform owners and product teams to connect ServiceNow with the wider enterprise ecosystem.

• Assess and oversee the integration of agentic AI and generative AI tools.

• Lead the introduction of new ServiceNow functionality and platform releases.

• Create reference architectures, reusable frameworks and templates to streamline solution delivery.

• Contribute to infrastructure architecture across cloud and on-premises environments.

• Coach ServiceNow engineers and promote shared architectural knowledge and practices.

Skillset

• At least 7 years' experience in enterprise or solution architecture, delivering large-scale systems across multiple business and technology domains.

• At least 3 years' experience designing ServiceNow architectures and leading complex implementations across multiple modules.

• Minimum of 3 years' experience with core ServiceNow capabilities, including Service Catalog, Flow Designer, Integration Hub, CMDB, Discovery, Performance Analytics and custom applications.

• Strong knowledge of key ServiceNow modules, particularly ITSM, ITOM, CSM or GRC.

• Experience designing enterprise integrations using REST, SOAP, JDBC or similar technologies.

• Hands-on development skills in JavaScript, ServiceNow scripting and Studio/App Engine.

• At least one year's experience with agentic AI architectures, AI skills development and enterprise applications of generative AI.

• Knowledge of security, compliance and DevOps principles, ideally supported by experience with CI/CD pipelines, GitHub Actions and automated deployments.

• Familiarity with AWS or GCP, cloud-native services, multi-cloud architectures and cloud migration strategies would be an advantage.

• Strong stakeholder communication skills, with the ability to translate business requirements into architectural solutions.

Benefits

• Salary: $110k - $140k.