Technical Engineer

Insight Global; Hyderabad; In loco; INR 900.000 - 1.500.000; Tempo pieno

Descrizione del lavoro

IG Labs seeks a Technical/Field Engineer to integrate our Factory solutions into diverse client stacks in India. You will run feasibility experiments, debug complex environments, and ensure deployments meet security and governance standards while delivering concrete, deployable results.

You will work alongside Solution Architects, Technical Architects, and Forward Deployed Engineers in a POD model, turning learnings into reusable patterns for future engagements and driving enterprise-grade

Competenze

• 8+ years in a deeply technical engineering role (solutions engineering, platform or systems engineering, complex integration, or similar).
• Fast at learning new stacks, frameworks, and platforms to real depth.
• Exceptional at debugging hard, ambiguous problems methodically.
• A solid command of security and governance in enterprise deployments: access control, data protection, audit, and compliance.

Mansioni

• Proving feasibility: build experiments and proofs-of-concepts to confirm work in a client’s environment.
• De-risk engagements early with clear, evidence-backed yes/no signals.
• Spike unknowns in a new stack and report what is possible, hard, and to avoid.
• Own the security and governance of AI deployments and ensure compliance with client requirements.
• Deliver end-to-end work from a hard technical question to a proven result for the engagement.
• Maintain documentation and handoff discipline for multi-client delivery.

Conoscenze

Deep debugging

Fast learner

Security governance

Written communication

Strumenti

Datadog

Grafana

APIs

Descrizione del lavoro

Proving Feasibility and Solving the Hardest Problems in the Client's Stack

Location: India

The Role

We are looking for a Technical/Field Engineer to make IG Labs' Factory and solutions work inside the client's own technology stack. Every client runs a different environment, often complex and highly specialized, and getting our solutions to run inside it takes deep, focused technical expertise. You are the specialist who brings it: you learn a client's stack fast, prove what is possible in it, and solve the hard, stack-specific problems that decide whether a deployment succeeds. This is core delivery engineering, the difference between a solution that ships and one that stalls.

You are the engine of feasibility. When the team needs to know whether something can actually be done in a client's environment, you build the experiment or proof-of-concept that answers it, fast, before anyone commits to a path that will not hold. And when an engagement hits a problem that needs deep, methodical debugging, the kind that takes real expertise and patience to unwind, that is your work to own. You also own how a deployment satisfies the client's security and governance requirements, so what proves feasible is also safe to put into production.

You are a distinct category in our delivery model. You are not the Solution Architect who sets the high-level design, the Technical Architect who owns the lower-level architecture, or the Forward Deployed Engineer who builds and deploys across the engagement. You bring depth where they bring breadth: the specific, hard-won command of a client's technology that an engagement lives or dies on. You are a senior engineer in our delivery organization, based in India, working within the POD model alongside the SAs, TAs, FDEs, and the Data and UI/UX engineers who build the rest of the system.

Everything you learn, you make reusable. The integration patterns, environment playbooks, and feasibility findings you produce become Factory IP, so the next time we meet a stack like this one, we start ahead instead of from scratch.

Key Responsibilities

Proving Feasibility

• Build the experiments and proofs-of-concepts that establish whether an approach can actually work in a client's environment, before the team commits to it.
• De-risk engagements early: turn an open technical question into a clear, evidence-backed yes or no, fast.
• Spike the unknowns in a new stack and report back what is possible, what is hard, and what to avoid.
• Give the Solution Architects, Technical Architects, and Forward Deployed Engineers the feasibility signal they need to scope and plan with confidence.

Deep Technical Problem-Solving

• Master unfamiliar client technology stacks quickly, becoming the engagement's depth on the client's specific systems and technologies.
• Figure out how to deploy IG Labs' Factory and solutions inside the client's specific environment, with its integrations and constraints and all.
• Own the hard, methodical debugging: the integration, compatibility, environment, and performance problems that take real expertise and patience to unwind.
• Persist where others stall, and stay with a problem until it is genuinely solved, not worked around.

Security & Governance

• Own the security and governance of our AI deployments: how the system handles data, access, and secrets, and the controls an enterprise requires.
• Make sure deployments meet the client's security posture and the regulatory constraints of their industry, with particular care in financial services and healthcare.
• Put the right controls around agentic systems: data protection and PII handling, access and permissions, audit and lineage, and the guardrails that keep autonomy within policy.
• Work with the client's security and compliance teams to get solutions approved and into production without cutting corners.

Delivering in Client Engagements

• Work as a peer to the Solution Architects, Technical Architects, and Forward Deployed Engineers in the POD, bringing the depth they rely on but do not carry themselves.
• Own your work end to end, from a hard technical question to a proven, working result the engagement can build on.
• Maintain the documentation and handoff discipline that distributed, multi-client delivery requires, so what you prove and solve is easy to pick up and reuse.
• Be available for the hard, real-time problems that need a working session, not a write-up.

Building Reusable Capability

• Turn everything you learn into reusable capability: integration patterns, environment playbooks, and feasibility findings that make the next engagement on a similar stack faster.
• Partner with the Technical Architect to abstract, validate, and document what you produce for the IP library.
• Actively drive Reuse Index, so the next time we meet a stack like this one, we start ahead instead of from scratch.
• Treat capability-building as core, not overhead. Every hard problem solved should leave the Factory stronger.

What This Role Is Not

• Not a Solution Architect. The SA sets the high-level solution design; you prove it can be built in the client's environment and make it work there.
• Not a Technical Architect. The TA owns the lower-level architecture and standards; you bring the deep, stack-specific expertise that turns architecture into something that runs.
• Not a Forward Deployed Engineer. The FDE builds and deploys across the engagement with broad range; you go deep on the client's specific technology and the hardest technical problems. Breadth and depth, side by side.
• Not a pre-sales or demo role. You are an engineer who proves feasibility with real code and solves real problems, not slideware.
• Not a support desk or ticket queue. You take the hard, novel technical problems, not routine requests.

Qualifications

Required

8+ years in a deeply technical engineering role (solutions engineering, platform or systems engineering, complex integration, or similar), with a track record of going into unfamiliar technology and making it work. Fast at learning new stacks, frameworks, and platforms to real depth. Exceptional at debugging hard, ambiguous problems methodically. Comfortable building proofs-of-concept quickly to prove or disprove an approach. Strong across the modern stack: cloud, APIs and integration, data, and the systems clients actually run. A solid command of security and governance in enterprise deployments: access control, data protection, audit, and compliance. A clear written communicator who collaborates well across a distributed team.

Strongly Preferred

Experience deploying software into enterprise client environments, especially regulated ones in financial services or healthcare. Breadth across multiple clouds and a wide range of technologies and languages. Experience with AI and agentic systems (LLM orchestration, RAG, agent runtimes). A consulting, professional services, or client-delivery background. Experience with AI governance and responsible-AI controls (guardrails, PII handling, model and data governance) and with security reviews in regulated environments. A reputation as the person teammates bring their hardest problems to.

Tools & Technology

Integration & APIs

REST, GraphQL, webhooks, OAuth, SSO, API gateways

Languages

Python, plus the fluency to pick up Java, Go, or TypeScript fast

Data & Storage

Profiling, tracing, log analysis, observability (Datadog, Grafana)

Containers & Deployment

Security & Governance

IAM, secrets management, data protection, audit and lineage, policy guardrails