GenAI Field Architect, Customer Value Engineering at Ema

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

8+ years in software/solutions architecture, including 3+ years with LLM or event-driven systems
Expert in Python, REST/JSON APIs, and cloud infrastructure (GCP, AWS, or Azure)
Proven record deploying AI systems in enterprise environments
Familiarity with agent frameworks like LangChain, Semantic Kernel

Responsibilities

Workflow Discovery & Solution Design: Lead discovery workshops to understand human workflows, pain points, data flows, and integration needs. Translate business objectives into AI architecture blueprints covering integration, data, security, and success metrics. Author and maintain “AI-Employee” design documents to guide implementation from blueprint to SLOs
Data Integration & Action Building: Use declarative connectors and APIs to ingest, normalize, and secure data from enterprise systems (CRM, ERP, ATS, etc.). Build and maintain reusable action blocks using REST/SOAP/RPA and integrate them into agent-based workflows
Agentic Reasoning & Prompt Engineering: Design and compose reasoning agents using modern frameworks (e.g., LangChain, Semantic Kernel). Tune prompts, set up memory management, and define mesh topologies to ensure robust agentic reasoning. Own prompt evaluation, experiment design (A/A, A/B), and rollback strategies
Human-AI Interaction: Define and implement user interaction flows by integrating with Slack, Microsoft Teams, widgets, or customer-facing apps. Ensure seamless handoff between automated and human-in-the-loop experiences
Monitoring, Metrics & Observability: Define success metrics, KPIs, and SLOs; wire them into dashboards, alerts, and observability systems. Steward observability packs, including Terraform/Helm configurations and alerting strategies
Security, Identity & Permissions: Enforce zero-trust identity patterns including SSO (Okta/AD) and RBAC. Own auditing, access control, and compliance posture across deployments
Collaboration & Continuous Improvement: Lead technical, architectural, and security reviews with internal teams and customer stakeholders. Partner with CVEs and system integrators to unblock issues and ensure deployment success. Monitor production system health and performance, lead continuous-improvement sprints, and codify learnings into reusable playbooks and runbooks. Maintain registries of versioned prompts, connectors, and action templates to support scale and reuse. Channel field insights to Product and ML teams to refine roadmap and platform capabilities

Skills

Key technologies and capabilities for this role

GenAIAI ArchitectureWorkflow DesignData IntegrationAPIsDeclarative ConnectorsSecuritySLOs

Questions & Answers

Common questions about this position

What is the salary for this GenAI Field Architect position?

This information is not specified in the job description.

Is this role remote or hybrid, and what are the office requirements?

This is a hybrid role requiring in-office work three days per week. Ema is headquartered in Silicon Valley with a second hub in Bangalore, India.

What key skills are required for the GenAI Field Architect role?

Key skills include leading workflow discovery and solution design, data integration using APIs and connectors, agentic reasoning with frameworks like LangChain or Semantic Kernel, prompt engineering, and expertise in monitoring, observability, and security.

What is the company culture like at Ema?

Ema features a high-caliber team of top engineers from Google, Microsoft Research, Facebook, Square, and Coinbase, along with alumni from Stanford, MIT, UC Berkeley, CMU, and IITs, founded by executives from Google, Coinbase, Flipkart, and Okta.

What makes a strong candidate for this GenAI Field Architect role?

Strong candidates excel in translating business objectives into AI architecture blueprints, building scalable agentic workflows with frameworks like LangChain, handling data integration from enterprise systems, and defining observability, security, and success metrics.

Ema

Develops enterprise AI solutions for workforce efficiency

About Ema

Ema develops and implements AI solutions specifically designed for businesses. Their main product is AI employees that can be customized through conversation to learn and perform tasks that exceed human capabilities, allowing companies to quickly expand their workforce. Ema's AI solutions focus on replacing traditional co-pilots with secure and compliant AI employees, meeting strict standards like SOC2, ISO27001, GDPR, HIPAA, and NIST. The EmaFusionTM model combines the strengths of over 100 large language models to deliver high accuracy at a low cost for various enterprise applications. Ema distinguishes itself from competitors by providing tailored solutions that empower businesses to enhance their operational efficiency. The company's goal is to help enterprises take control of their operations and achieve significant improvements in productivity through advanced AI technology.

Mountain View, CaliforniaHeadquarters

2023Year Founded

$59.3MTotal Funding

SERIES_ACompany Stage

Cybersecurity, AI & Machine LearningIndustries

51-200Employees

Benefits

Hybrid Work Options

Risks

Emerging competition from startups like SilkFlo and Kognitos threatens Ema's market share.

Rapid customer base expansion may strain Ema's operational capabilities and service quality.

Reliance on multiple investors may lead to conflicting interests and strategic directions.

Differentiation

EmaFusionTM integrates over 100 LLMs for high accuracy and cost-effectiveness.

Ema offers secure AI employees adhering to SOC2, ISO27001, GDPR, HIPAA, and NIST standards.

Ema's no-code AI agents enable enterprises to deploy AI without extensive technical expertise.

Upsides

Ema's customer base has more than doubled since its launch in March 2024.

Ema secured $50M in Series A funding, enhancing its market position and capabilities.

Growing demand for AI-driven automation aligns with Ema's focus on AI employees.

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