Senior AI Applications Engineer

Ema•San Francisco Bay Area, CA

About The Position

Ema is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the Universal AI employee. We are founded by ex-Google, Coinbase, Okta executives, and serial entrepreneurs. We’re well-funded by the top investors and angels in the world. Ema is based in Silicon Valley and Bangalore. The Senior AI Application Engineer will be pivotal in providing world-class post-deployment support for Ema’s Agent Assist/Chatbot product. This role requires a strong blend of technical expertise and customer-focused problem-solving. You will configure, troubleshoot, and optimize AI solutions for our customers, ensuring high performance, continuous improvement of customer workflows, and exceptional customer satisfaction. You will independently manage complex deployments and solutions for enterprise customers with minimal guidance.

Requirements

4+ years of software engineering experience.
Significant experience in AI/LLM application development, including building agents, integrations, workflows, and evaluating/improving their performance.
Demonstrated the ability to manage complex deployments & solution design for an enterprise customer independently with minimal guidance.
Strong troubleshooting and problem-solving skills, especially in production environments.
Excellent communication skills to collaborate effectively with both technical and non-technical stakeholders.
Proficiency in Python & SQL scripting.
Experience with prompt engineering techniques.
Proficient at invoking platform APIs to retrieve or push data, configure workflows.
Familiarity with JSON, REST, SOAP or other integration protocols.
Data-driven evaluation skills, including setting up and interpreting A/A experiments.
Familiarity with logging, dashboard creation, and alerting tools.
Takes responsibility for ongoing workflow management and customer outcomes.
Actively explores new GenAI/automation techniques and best practices to enhance workflows.
Works effectively across multiple teams.
Prioritizes customer success criteria, ensuring solutions address real business needs.

Nice To Haves

Experience setting up, configuring, and supporting ML Systems or AI Agents is a plus.
Experience in building LLM-based evaluation frameworks & conducting UATs with real customers.
Familiarity with key support metrics (FRT, AHT, TAT, CSAT) and reporting.
Ideal candidates should be able to troubleshoot ML performance issues & recommend solutions to improve accuracy metrics & other business KPIs.
Understanding of Data Structures & Algorithms is a plus.
Familiarity with integrating common CRMs/ATS tools would be a plus.

Responsibilities

Configure and integrate AI/GenAI workflows using platform APIs and customer data, ensuring smooth and secure deployment.
Translate customer requirements into technical solutions, validating workflow correctness and continuously refining prompts for optimal performance.
Develop and automate tasks using Python & SQL, and build prototypes using open-source Agentic Frameworks to streamline CX workflows.
Design, run, and analyze A/A experiments to measure and improve workflow quality and reliability.
Monitor AI workflows using business metrics and observability dashboards, quickly responding to issues to ensure high availability.
Provide proactive solutions and regular updates to customers, maintaining high CSAT through effective troubleshooting and communication.
Diagnose and resolve platform issues related to APIs, data integration, and workflow configurations, collaborating with engineering when needed.
Utilize APIs and integration protocols (JSON, REST, SOAP) to configure workflows and integrate with CRM/ATS tools.
Write custom scripts to query databases and create reports for in-depth analysis and to demonstrate ROI to customers.

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