Forward Networks VP Role Pays Up to $380k Amid Hiring

Hiring Accelerates Without Fanfare

Forward Networks posted six distinct roles on its job board — a velocity that signals a coordinated go-to-market build-out, not routine backfill. The openings span customer success, sales engineering, business development, and revenue operations, with base salaries clustering between $165,000 and $380,000. That spread, and the geographic distribution from Santa Clara to Indianapolis, signals a company building out its go-to-market engine while deepening technical coverage in the field.

Zero G Talent's board data shows Forward Networks' salaried roles typically band $188k–$364k with a $300k median — the new postings sit comfortably inside that range, with the VP role stretching the top end, as Zero G Talent's data shows.

What distinguishes this cluster is the mix. Customer success and sales engineering roles outnumber pure engineering posts, and the revenue analyst position points to an organization instrumenting its own growth. The Indianapolis BDR role, the only non-coastal listing, hints at a deliberate push into mid-market accounts that don't sit on the usual tech corridors. Together, the postings read less like replacement hiring and more like a coordinated build-out: leadership to define the motion, managers to scale it, field engineers to carry the technical conversation, and operations to keep the pipeline measurable.

Forward Networks has not issued a press release announcing a funding round or headcount target. The signal comes from the job board postings. In a market where placement firm Challenger, Gray & Christmas describes hiring plans as "historically low" compared to pre-pandemic levels, that tempo stands out. The unemployment rate holds at 4.1 percent, and the wage premium for changing jobs has fallen below 2 percent, down from 8.4 percent a few years ago. Companies with genuine demand are moving fast; the rest are waiting.

The salary transparency is also notable. At least 14 states now require pay ranges in postings, and many multi-state employers disclose nationally to comply. Forward Networks lists bands for most salaried roles in this batch.

The Product That Drives the Hiring

Forward Networks was founded in 2013 by four Stanford Ph.D.s — David Erickson, Brandon Heller, Peyman Kazemian, and Nikhil Handigol, who started with a single question: does the network actually behave as intended, by design, in production, and across changes? The answer, they concluded, required more than visibility. It required a mathematically accurate model of the network itself. Headquartered in Santa Clara, California, the company has raised backing from MSD Partners, Goldman Sachs, Andreessen Horowitz, Threshold Ventures, Section 32, Omega Venture Partners, and A. Capital.

The core product, Forward Enterprise, builds what the company calls a network digital twin — a mathematically precise virtual replica of an organization's entire network across on-premises, hybrid, and multicloud environments. Unlike monitoring tools that sample or approximate, the platform collects and analyzes the real configuration and state of every device, path, and policy across routers, switches, firewalls, load balancers, SD-WAN, wireless controllers, and all major public clouds. It supports more than 30 hardware vendors, over 35 operating systems, and upwards of 900 OS versions. The collector software runs on-premises, logging into network devices via SSH to gather running configuration as well as routing and forwarding state, then sends that data to the cloud instance for modeling. The approach is read-only, guaranteeing security while allowing teams to analyze and verify configurations without risk.

That modeling engine calculates every possible path a packet can take. It discovers unknown devices, integrates with CMDBs, and produces a single source of truth that NetOps and SecOps teams can share, replacing the spreadsheets, tribal knowledge, and guesswork that a senior director of network and security architecture at a leading financial services company described as the status quo before Forward. The platform's unique collection process delivers current, actionable insights into network behavior, security posture, and compliance status.

In January 2026, the company introduced Forward AI, a natural-language layer atop the digital twin that lets network, security, and cloud teams ask complex questions, understand behavior, validate outcomes, and safely automate workflows. Built on the same mathematically accurate foundation, Forward AI establishes a foundation for agentic AI in network operations by delivering validated, evidence-backed recommendations. Each result includes clear evidence so teams can inspect underlying data and reasoning, validate outcomes, and act with confidence. Support for the Model Context Protocol (MCP) extends that verification foundation to enterprises and third-party developers building their own agentic tools. General availability was released in April 2026.

The market has taken notice. GigaOm has ranked Forward Networks an Outperformer in its Radar for Network Validation for four consecutive years as of December 2025, citing release cadence, agentic AI integration, enhanced vulnerability analysis, firewall policy normalization, and comprehensive attack surface capabilities. The 2025 Radar evaluated 24 vendors over a 12–18 month horizon. Customers include Goldman Sachs, PayPal, S&P Global, IBM, Dell, other Fortune 500 enterprises, fast-growing companies, and government agencies. An IDC report found the average Forward customer experiences $14.2 million in annual benefits through improved efficiency and security.

In July 2025, Forward joined the Infoblox Technology Alliance Partner Program with a certified integration for Infoblox NIOS DDI. The partnership addressed a concrete migration path: Infoblox's legacy NetMRI reached Last Order Date on April 30, 2025, with end-of-support scheduled for April 30, 2027. Forward Enterprise is positioned as a certified NetMRI replacement, offering seamless migration, enhanced visibility across hybrid multi-vendor environments, and improved IPAM accuracy.

Zero-trust architecture verification has been part of the platform since at least 2021, when the company unveiled features enabling security engineers to determine blast radius of compromised devices immediately, create an always up-to-date zone-to-zone security matrix, and simplify vulnerability remediation. As Chiara Regale, SVP of Product and UX, said in December 2025: "Networks are now too complex for guesswork, especially as AI becomes part of every workflow. Agentic operations demand accurate data sources and precise guardrails."

That complexity is the hiring signal. IT organizations are accelerating AI adoption and modernization while headcount remains largely flat, placing new pressure on teams to sustain reliability and security at scale. The platform's breadth means the engineers who build, sell, and support it need deep protocol knowledge, multi-vendor configuration fluency, cloud networking expertise, and increasingly, the ability to reason about agentic AI workflows grounded in mathematically verified network state.

Why Verification Talent Is Scarce

The hiring surge at Forward Networks does not sit in isolation. It reflects a broader recalibration across infrastructure teams: networks have grown too complex, too distributed, and too business-critical to operate on intuition and manual troubleshooting. The same forces pressing banks, cloud providers, and enterprises to harden identity verification — AI-enabled fraud, regulatory mandates for provenance, the shift toward agentic automation — are pressing network operators to prove, continuously, that their topologies behave as intended.

Deloitte's 2024 technology predictions frame the verification imperative starkly. Analysts estimate the global deepfake-detection market will compound at 42 percent annually, rising from US$5.5 billion in 2023 to US$15.7 billion by 2026. That figure tracks media and social platforms, but the underlying driver, generative AI making synthetic media trivial to produce, extends to network telemetry.

Deloitte notes that "on the enterprise security side, companies across industries should be aware that gen AI can make social engineering attacks more effective and can compromise some authentication measures," and that "it may be necessary to implement additional verification layers, especially for video and audio-based processes." Network verification is the infrastructure analogue of those layers: a mathematical proof that the control plane matches the intended design, not just a sampling of monitoring data.

Regulatory momentum reinforces the trend. California's proposed AB-3211 would require device firmware to embed provenance metadata in photos and platforms to disclose it; the EU AI Act revisions mandate clear labeling of AI-generated content and deepfakes. Both regimes treat verifiable provenance as a compliance baseline. In networking, that baseline translates to continuous assurance — evidence that every path, policy, and failure domain conforms to spec, auditable at any moment.

The Coalition for Content Provenance and Authenticity (C2PA), now backed by Deloitte and major tech firms, records every lifecycle step of an image through a tamper-evident log. Forward Networks' core technology applies the same principle to network state: a digital twin that records every configuration change, every path computation, every policy decision, and can replay or verify any prior state.

The talent market is already signaling the shift. CompTIA's Network+ certification (updated to version V9 in June 2024) now examines candidates on network connectivity, documentation, service configuration, data centers, cloud, virtual networking, monitoring, troubleshooting, and security hardening. That syllabus reads like a job description for a verification engineer: the exam expects fluency in the very domains where manual CLI skills no longer scale. Meanwhile, the financial sector offers a leading indicator. U.S. regulators issued significantly more Bank Secrecy Act and AML enforcement actions in fiscal 2024 than the prior year, and banks filed a record 2.6 million suspicious activity reports — 7,100 per day.

The same imperative drives network teams: compliance auditors now ask for proof of segmentation, proof of encryption-in-transit, proof that a change window did not drift — proof that only a verification platform can supply continuously.

Deloitte's 2025 banking outlook argues that "agentic AI offers breakthrough potential, but only if supported by AI-ready data, accurate, timely, broad, and securely governed," and that "autonomous agents cannot thrive on siloed or disorganized data."

Agentic AI adds a third vector. Network verification produces exactly that grade of data: a structured, queryable, mathematically grounded model of the entire fabric. When an autonomous remediation agent proposes a config push, the verification layer is the gate that says yes or no. Without it, the agent is guessing; with it, the agent operates on ground truth.

Forward Networks' open roles map to this demand curve. The salary band reflects the scarcity of engineers who can translate verification theory into customer outcomes. The market is not hiring for monitoring; it is hiring for proof.

Skills the Platform Demands

Candidates who work with Forward Networks' technology demonstrate fluency in three layers: the protocols that move packets, the cloud abstractions that obscure them, and the verification logic that proves the network behaves as designed. The following distills what the product requires, based on its documented capabilities.

Protocol fundamentals. BGP, OSPF, IS-IS, and EIGRP are table stakes; the platform models how a prefix traverses route-map manipulation, community filtering, and VRF leakage. VXLAN/EVPN overlay fabrics, SRv6, and segment-routing traffic engineering appear in the hybrid multicloud topologies Forward Enterprise models for customers such as Goldman Sachs, PayPal, and S&P Global. Engineers who have stitched an on-premises leaf-spine fabric to an AWS Transit Gateway and an Azure Virtual WAN, then written a validation query that proves subnet reachability across the stitch, speak the language the platform uses.

Cloud networking. Forward Enterprise collects state from AWS, Azure, Google Cloud, and Oracle Cloud as first-class citizens, normalizing security groups, route tables, and firewall policies into the same mathematical model used for physical gear. The GigaOm Radar calls out "Hybrid Multicloud Awareness" as a five-star capability; engineers who have debugged a black-holed flow across a Direct Connect and an ExpressRoute circuit in the same week operate in the domain the product covers.

Verification and intent-based tooling. Forward Networks' own data-plane verification tests connectivity properties, such as subnet reachability, VLAN consistency, and MTU alignment, against a declared intent model. A portfolio artifact that defines intended state in YAML (or the vendor's native policy language), pulls live config via NETCONF/RESTCONF/gNMI, runs a diff, and emits a remediation plan demonstrates the workflow. Tools such as Batfish, pyATS, or Nautobot can approximate the workflow; the point is to prove you think in terms of continuous validation, not one-time audits. The 2025 GigaOm report also highlights "firewall policy normalization" and "comprehensive attack surface capabilities," so a rule-set analysis that detects shadowed rules, overly permissive zones, and cross-zone leakage across a multi-vendor firewall estate aligns with the platform's capabilities.

Security verification. ** Forward AI, released in April 2026, layered a conversational interface on the digital twin so SecOps teams could ask "which devices can reach the PCI segment?" and receive evidence-backed answers. Familiarity with the MITRE ATT&CK framework mapped to network mitigations, such as micro-segmentation, zero-trust segmentation, and lateral-movement detection via flow telemetry, aligns with the use cases the platform addresses. A detection rule that correlates NetFlow anomalies with a vulnerability scan result, documented with the query and the false-positive reduction achieved, makes the conversation concrete.

Agentic AI integration. Forward AI exposes its verification foundation through the Model Context Protocol (MCP), allowing third-party agents to query the digital twin with guardrails. Experimenting with MCP servers locally by wrapping a read-only network query (e.g., "show all paths between VLAN 100 and the internet gateway") in an MCP tool definition, then invoking it from a language model, demonstrates understanding of the boundary between "the model answers" and "the model acts," which aligns with Forward's emphasis on keeping humans in the loop for critical infrastructure.

Soft-skill translation. Roles spanning Customer Success Engineer, Senior Systems Engineer, and VP of Customer Success & Adoption all require translating mathematical certainty into business outcomes. A five-minute narrative, "Here is a network behavior the customer assumed was true, here is what the digital twin proved, here is the change we validated before deployment, here is the risk avoided," using the vocabulary of the platform (digital twin, intent, verification, evidence, guardrails) aligns with how the company describes its own value proposition.

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