Forward Deployed Engineer

Company: Trida Labs

Location: Hyderabad, India

Employment Type: Full-time

Experience: 3–5 Years

About Trida Labs

Trida Labs builds AI-native products that help organizations work with enterprise data, analytics, and intelligent applications.

Our products include TridaPad, an AI-native data collaboration platform for querying, analyzing, visualizing, and managing enterprise data; AgentSQL, an agentic AI analytics solution for natural-language interaction with enterprise data; and TridaPad MCP Server, which enables AI assistants and MCP-compatible clients to interact with TridaPad capabilities.

About the Role

We are looking for a Forward Deployed Engineer to work directly with customers and turn business and technical requirements into working solutions using Trida Labs products.

You will work across customer discovery, data integration, configuration, testing, deployment, and production troubleshooting. You will understand customer workflows, data environments, security requirements, and business needs, then configure and integrate our products to solve real-world problems.

You will also support customer pilots, technical demonstrations, and pre-sales engagements, validating solutions against customer-specific use cases and collaborating with engineering teams when product-level changes are required.

This is a customer-facing engineering role focused on configuring and extending existing capabilities rather than building customer-specific forks.

What You'll Do

1. Customer Discovery & Solution Design

- Understand customer workflows, technical requirements, data environments, and operational constraints.
- Translate business requirements into practical Trida Labs solutions.
- Identify required data sources, integrations, permissions, configurations, and deployment requirements.
- Assess technical feasibility, explain trade-offs, and define reusable implementation approaches.

2. Pre-Sales, Pilots & Proofs of Concept

- Support technical discussions, product demonstrations, pilots, and proofs of concept.
- Demonstrate how TridaPad and AgentSQL address customer use cases.
- Configure representative customer environments and validate technical requirements.
- Identify integration, security, and deployment constraints and communicate findings to relevant stakeholders.

3. Product Implementation & Data Integration

- Deploy and configure TridaPad and AgentSQL for customer requirements.
- Configure data sources, database connections, permissions, schemas, and analytics workflows.
- Integrate enterprise databases and platforms such as PostgreSQL, MySQL, SQL Server, MongoDB, Snowflake, BigQuery, and Databricks.
- Understand customer data models, relationships, and business metrics.
- Validate data accessibility and troubleshoot connectivity, permission, schema, query, and integration issues.

4. AI & Analytics Implementation

- Configure existing AI and analytics capabilities for customer use cases.
- Adapt prompts, context, tools, and application workflows where appropriate.
- Validate natural-language analytics, SQL generation, analytical results, visualizations, dashboards, and summaries.
- Diagnose unreliable AI outputs and distinguish data, configuration, context, model, and product issues.
- Collaborate with specialist engineering teams when core product changes are needed.

5. Security, Access & MCP Integrations

- Support customer security questionnaires, technical reviews,



and access requirements.
- Coordinate VPN, IP allowlisting, private connectivity, restricted network, and other environment-specific requirements.
- Support self-hosted deployments in customer cloud or on-premises environments where applicable.
- Apply least-privilege principles and follow requirements for handling production data, PII, credentials, logs, and debugging information.
- Configure and validate MCP integrations with AI assistants, internal applications, and customer workflows, including authentication, permissions, and tool access.

6. Customer Evaluation & Validation

- Build customer-specific golden question sets containing representative business questions, expected SQL, and verified analytical results.
- Test customer configurations against schemas, terminology, metrics, permissions, and real-world questions.
- Rerun relevant tests after product, model, prompt, or configuration changes.
- Validate SQL, analytics, visualizations, dashboards, and summaries against expected outcomes.
- Track regressions, communicate actionable findings, and maintain versioned customer-specific configuration artifacts.

7. Deployment & Production Troubleshooting

- Prepare implementation plans and technical validation checklists.
- Support deployments across development, staging, and production environments.
- Troubleshoot application, API, database, AI, integration, and deployment issues using logs, traces, errors, and reproduction steps.
- Validate fixes against customer-relevant scenarios and support releases, upgrades, and post-deployment checks.
- Coordinate infrastructure and platform-level issues with the appropriate engineering teams.

8. Customer Feedback & Engineering Collaboration

- Identify recurring customer problems and distinguish implementation needs from core product requirements.
- Provide structured feedback with technical details, reproduction steps, expected behavior, and customer impact.
- Identify opportunities to convert repeated implementation work into reusable product capabilities, tools, or documentation.
- Collaborate with AI, AI Agent, Data & AI, Backend, Platform, NLP/ML, and Product teams.
- Reduce customer-specific workarounds and avoid unnecessary product forks.

Role Ownership

- Forward Deployed Engineer: Owns customer discovery, solution design, implementation, integration, configuration, validation, deployment, troubleshooting, and customer-facing technical delivery.
- AI Engineer: Owns reusable user-facing AI features and AI-powered application experiences.
- AI Agent Engineer: Owns agent orchestration, behavior, tool workflows, and core agent capabilities.
- Data & AI Engineer: Owns data connectivity, schema and metadata systems, semantic representations, and cross-database data correctness.
- NLP/ML Engineer: Owns model-level NLP and generation quality, including SQL-generation capabilities.
- Platform Engineer: Owns infrastructure, model access, deployment systems, observability, security, and platform-level connectivity.
- Backend Engineer: Owns core backend services, APIs,



business logic, and shared application services.

The Forward Deployed Engineer configures and extends existing capabilities, validates customer deployments, and escalates core product changes to the appropriate teams rather than maintaining customer-specific forks.

Customer Engagement Expectations

- Work directly with customers across different technical and business environments.
- Support customer meetings and deployments across relevant time zones when required.
- Be willing to travel for customer meetings, workshops, deployments, and go-live activities when necessary.
- Manage multiple implementation activities while maintaining clear priorities and communication.

What We're Looking For

- 3–5 years of experience in software engineering, solutions engineering, data engineering, AI engineering, technical consulting, or a related technical role.
- Strong proficiency in Python and SQL.
- Experience with APIs, databases, backend services, enterprise applications, and data integrations.
- Strong understanding of data workflows, SQL, and technical troubleshooting.
- Experience working with customers, stakeholders, or cross-functional technical teams.
- Familiarity with LLMs, Generative AI, and AI-powered applications.
- Ability to translate customer requirements into practical technical solutions.
- Solid debugging, analytical, and problem-solving skills.
- Ability to investigate issues using logs, errors, configurations, and reproduction steps.
- Strong communication skills and comfort supporting customer environments and production deployments.
- Ability to manage multiple requirements and competing priorities effectively.

Preferred Qualifications

- Experience in Forward Deployed Engineering, Solutions Engineering, Sales Engineering, Technical Consulting, or Technical Implementation.
- Experience supporting product demonstrations, pilots, or proofs of concept.
- Experience with AI analytics, natural-language-to-SQL, or enterprise data applications.
- Experience with AI agents, tool calling, or agentic workflows.
- Familiarity with LangGraph, LangChain, or LlamaIndex.
- Experience with MCP and AI assistant integrations.
- Experience with PostgreSQL, MySQL, SQL Server, MongoDB, Snowflake, BigQuery, or Databricks.
- Experience with Docker and cloud or deployment platforms such as AWS, Azure, GCP, Render, or Vercel.
- Experience with production deployments, AI evaluation, regression testing, observability, or production AI troubleshooting.

Key Skills Python | SQL | APIs | Databases | Enterprise Data | System Integration | Generative AI | LLMs | AI Applications | Natural-Language-to-SQL | Data Analytics | AI Agents | MCP | Docker | Cloud | Customer Deployment | Production Troubleshooting | Technical Implementation | Technical Communication

Why Join Trida Labs?

At Trida Labs, you will work directly on real AI systems solving enterprise data and analytics problems.

You will collaborate with customers and engineering teams across solution design, AI implementation, enterprise data integration, evaluation, production troubleshooting, and product improvement—helping turn real customer requirements into reliable, reusable product capabilities.

Equal Opportunity

Trida Labs is an equal opportunity employer. We are committed to creating an inclusive workplace where diverse perspectives are valued and everyone has the opportunity to contribute and grow.

📌 Forward deployed Engineer (Hyderabad)
🏢 Trida Labs
📍 Hyderabad