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Forward Deployed Engineer

Coralogix
2 days ago
Full-time
On-site
Gurugram, Haryana, Israel

About Coralogix

Coralogix is a full-stack observability and security platform - logs, metrics, traces, and SIEM analysed in-stream at petabyte scale, stored in the customer's own data lake, and increasingly driven by our agentic AI layer (AI agent Olly, MCP server, CLI). Founded in 2015, headquartered in Boston, and backed by leading investors including Advent International, Brighton Park Capital, and Greenfield Partners with over $500M in funding.

What sets Coralogix apart as a platform to build on is the combination of data depth and architectural openness. Because the platform's architecture makes full-fidelity retention viable at scale, customers hold their complete operational and security picture in their own data lake - no sampling, no gaps, no third party holding the keys. Every layer is then programmatic - APIs, SDKs, and dev tools built for custom solutions - creating an unusually rich and open foundation for the work ahead.ating requisitions 'from scratch'

The role

Our most strategic customers need more than a platform. They need an engineer who deploys, customizes, and builds alongside them. Enterprise environments are complex - multiple clouds, legacy infrastructure, custom deployments, multiple tools - and what these customers need often extends well beyond what any platform delivers as standard.

The Forward Deployed Engineer closes that gap. You are an engineer embedded in Tier-1 accounts, working at the edge of what customers need next - requirements that evolve continuously as enterprises scale, innovate, and push the boundaries of what observability and security can do for them. This is field-deployed R&D. It is not account management and it is not support.

What you will do

Every engagement starts by getting to the real problem - translating an ambiguous or evolving customer requirement into a concrete, scoped technical plan before a line of code is written. You build the new functionality that emerges from evolving customer requirements - net-new use cases with a clear path to other customers and/or back to the product, customisations that extend existing capabilities where out-of-the-box configurations fall short, and critical features that unlock adoption or expansion with strategic accounts. You build in production-grade code, not prototypes, working closely with both in-house and customer observability and security teams - you build, they define the logic - ensuring domain validity in everything that ships. AI is central to both how you build and what you build: as a development accelerator and as the core ingredient in your solutions, with a particular focus on autonomous, multi-step agentic AI workflows. Every engagement is engineered for repeatability, and you work closely with R&D throughout - feeding back field patterns and the solutions you have built - so the best of what you ship is assessed, hardened, and absorbed into the platform. You are accountable for the outcomes in your accounts, not just the builds - adoption, retention, and time-to-value are yours to move.

How you will work

Own 2-3 strategic accounts (a single account during intensive deployments), operating across the full stakeholder range within each - from individual engineers and security analysts to CTOs and CISOs. Spend roughly 60-70% of your time in deep customer engagement, on-site and virtual, and the remainder on reusable playbooks and structured product feedback to R&D. Partner with Account Executives and Account Managers, who own the commercial relationship. Exercise judgment on scope continuously - deciding what matters now versus later, pushing back where needed, and knowing when something is ready to ship so the customer gets real value quickly. Your engagements are time-bounded with clearly defined outcomes.


  • 10+ years in software engineering writing production-grade code. Prior security or observability experience is a big plus, not a requirement - you will be paired with experts who provide the domain logic - but you must ramp quickly into unfamiliar domains.
  • A product-minded engineer with experience designing and building software products end to end - translating customer needs into product decisions, thinking in user experience and outcomes, and working fluently with modern AI development tools to build AI-native solution
  • Proven customer engagement experience across both technical and non-technical audiences, including at C-level - able to build rapport quickly, explain complex concepts credibly, and navigate an enterprise organisation to get things done.
  • Operates with founder-level ownership: high urgency, comfort with ambiguity, and the ability to define the problem as much as solve it.
  • A genuine blend of engineering depth and strategic-consulting instinct.
  • Based in-region, with significant on-site time at customer sites.

Strong plus: detection engineering or security-operations background; hands-on experience building agentic or LLM-based systems in production, including familiarity with MCP; developer-platform or SDK building; prior resident-engineer, forward-deployed, or strategic-engineering experience at an observability, data-infrastructure, or security vendor.

What success looks like

Replicable use cases delivered and subsequently absorbed into the product; improved time-to-value for new enterprise onboarding where you are deployed; stronger retention among your accounts versus baseline; and expansion revenue directly attributable to the capability you have built.

How we work

This is a new function - a small, elite team with a founding mandate. We are entrepreneurial and high-intensity, operating with unreasonable agency. If you want the deepest applied AI, observability and security engineering work available - building real solutions for the most demanding enterprise environments, seeing your field-proven patterns absorbed into a platform used by thousands of engineers globally - this is where that happens. Think of it as your PhD in applied AI, observability and security: no academic benchmarks, only production.