Careers at Obviant: Teams, Pay and How to Get Hired

Who Gets Hired and Onto Which Teams

The defense acquisition market runs on paperwork — thousands of contract vehicles, program records, and regulatory filings no single human can synthesize. Obviant exists because that synthesis gap has become a strategic liability. The company builds AI-driven decision systems that ingest this firehose and surface the signals program managers, policy shops, and contractors need to move faster. That mission shapes every hiring decision: they need engineers who ship reliable software in classified environments, analysts who speak the language of defense acquisition, and product leaders who translate mission needs into roadmaps without losing the thread.

As of October 2026, Obviant lists eight open roles across two hubs: six in Arlington, Virginia and two in Tampa, Florida, all full-time and heavily weighted toward senior contributors. Engineering carries five openings: two Senior Fullstack Software Engineer positions (one per location), two Senior Engineering Manager roles (also split Arlington/Tampa), and a Senior Product Manager in Arlington. The remaining three slots sit in analytics and go-to-market: an Analyst - Defense Acquisition, a Senior Data & BI Automation Analyst, and an Account Executive, Commercial, all in Arlington. Six roles are hybrid; the two Tampa positions require in-office presence, driven by clearance and collaboration demands.

The composition tells a clear story. Roughly 71 percent of open roles sit at senior level, another 29 percent at lead/manager level — no junior or mid-level openings appear. That skew isn't accidental. The tech stack touches classified networks (TS/SCI appears on multiple postings), the data pipeline ingests messy government sources at scale, and the product serves users who measure success in program outcomes, not user engagement metrics. Founders Brendan Karp and Dylan Taylor have structured the organization around small, high-autonomy teams that own end-to-end capabilities: a backend-heavy engineering core, a product function close to defense customers, and an analytics layer that turns raw acquisition data into platform features. The Tampa hub, newer and smaller, mirrors the Arlington structure with its own engineering manager and fullstack lead — suggesting deliberate replication, not a satellite office.

Geography matters. Arlington puts the team inside the Beltway, near the program offices and prime contractors that constitute both Obviant's user base and talent pool. Tampa aligns with the region's growing defense-tech corridor (MacDill AFB, SOCOM, and a cluster of mission-focused startups) and gives the company a cleared-engineering bench outside the DC cost structure. Both locations operate hybrid by default, with Tampa roles explicitly in-office. The split reflects a practical calculation: the work requires whiteboarding sessions with cleared teammates and access to SCIF-adjacent infrastructure, but the company doesn't mandate five-day weeks for roles that can ship code remotely.

What's absent from the board is as telling as what's present. No DevOps, no security engineering, no dedicated ML roles — yet. The openings suggest Obviant is still in a build-and-harden phase for its core platform, staffing the product and engineering leadership that will define the architecture before layering on specialization. The analytics hires signal the data ingestion and normalization layer is mature enough to need dedicated ownership. The single commercial sales role hints at a go-to-market motion still founder-led or channel-dependent. For candidates, the message is legible: Obviant hires builders who operate in ambiguity, hold a clearance, and translate between defense bureaucracy and modern software practice. The next section breaks down what that translates to in compensation.

What It Pays

Obviant's compensation sits in a narrow, senior-heavy band that reflects a seed-stage defense-tech company paying for experience over headcount. The aggregated data from the three salaried roles currently listed shows a typical range of $154k–$219k with a median of $215k, a figure that aligns with the company's own posted ranges but runs above the $173k median ($160k–$193k) that Recruiting from Scratch calculated from 12 public postings spanning 2025–2026. The gap is explainable: the board captures only live, salaried engineering and product roles, while the broader scrape includes analyst and designer positions that pull the median down.

The clearest signal comes from the postings themselves. Seven roles carry explicit salary ranges, all senior level, split between Arlington and Tampa:

Two patterns stand out. First, location carries a $20k–$30k premium for Arlington over Tampa on identical titles — the Arlington fullstack band tops out at $215k per the board posting, versus $200k in Tampa, and Alion's data shows the engineering manager range shifts upward by roughly $15k at the floor and $27k at the ceiling. That delta tracks with office-level averages calculated from current postings: Arlington shows a $218k average salary across six open roles; Tampa shows $200k across two. Second, engineering management roles have the widest spreads, spanning $130k–$143k from floor to ceiling, which suggests Obviant is calibrating for scope (team size, P&L ownership, customer-facing responsibility) rather than title alone.

The board's three salaried roles (two senior fullstack engineers and one senior product manager) all fall inside the $154k–$219k band, with the product manager role commanding the highest ceiling at $220k. That matches the Alion aggregate's 'highest paying role' designation for Senior Product Manager at $220k. Notably, no junior or mid-level roles appear on the board; every opening is senior, and the analyst roles (which sit below the $154k floor) are absent from the board's live listings entirely. This reinforces the hiring plan described in Section 1: Obviant is buying senior capacity, not building a pyramid.

Equity and variable cash are not disclosed in any board postings or LinkedIn-sourced ranges (which show base only: $150k–$200k for Tampa fullstack as of October 2026; $170k–$215k for Arlington fullstack as of August 2026). The $7.1M seed round closed June 2025, led by Shield Capital with Motivate, A*, New Vista, Aloft, and Underdog Labs participating — a raise that typically funds 18–24 months of runway for a team this size. Candidates should assume standard early-stage equity grants (ISO options, 4-year vest, 1-year cliff) and ask directly about refresh cadence and liquidity events; the board data doesn't capture it.

Compared to peers in the defense-data space (Modern Intelligence, Albedo, Arcfield), Obviant's cash compensation is competitive. The trade-off Obviant offers is proximity to the acquisition decision loop: the platform ingests J-Books, appropriations tables, and program documents to map capability gaps to funding streams in near real time. For engineers who want their code to shape what gets bought, not just how it gets built, the compensation package includes a mission multiplier that doesn't show up in the base number.

How the Hiring Process Works and What Gets Candidates Through It

Obviant runs a hiring process that reflects its size (roughly 50 to 250 employees across Tampa and Arlington) and its mission focus. Loopcv.pro benchmarks put small businesses in the 3–6 week range from first contact to offer, with one or two interview rounds plus reference checks. That matches what candidates report on 1point3acres: a recruiter screen, then a compressed set of technical and behavioral rounds that emphasize culture fit alongside coding and system design ability.

The first touch is typically a recruiter phone screen — 15 to 30 minutes verifying basics: clearance eligibility, citizenship, and whether the candidate's stack aligns with the team's needs (Python, TypeScript, React, PostgreSQL appear across the postings). Candidates who clear that step move to a hiring manager conversation, 30–60 minutes, where the focus shifts to project ownership and how the candidate thinks about reliability in constrained environments. Loopcv.pro data notes this stage usually schedules within a week of the recruiter screen at most companies; Obviant's lean structure suggests it moves faster.

Technical assessment comes next. A verified 2026 interview report from 1point3acres lists three pillars: coding, system design, and behavioral. This mirrors the Loopcv.pro framework where Stage 4 (technical assessment) adds 3–7 days, and Stage 5 (panel or team interview) runs 1–3 rounds of 30–60 minutes each.

Reference checks follow the final interview (3–7 days per the benchmark), and background checks add another 3–14 days given the defense context. The clearance piece is the wildcard: federal roles can stretch 6–18 months for full clearance, but Obviant's postings require the ability to obtain and maintain a TS/SCI clearance. The board's salary band and the spread across engineering, product, and analyst roles indicate the company hires in cohorts, not one-offs, which means the process runs on a rhythm: batches of candidates move through stages together.

What gets candidates through? Three filters. First, demonstrable experience building systems that stay up when inputs are noisy — the Senior Data & BI Automation Analyst role calls for automation that reduces manual review cycles. Second, fluency with the defense acquisition lifecycle or willingness to learn it fast; the Analyst - Defense Acquisition posting makes that explicit. Third, communication that translates technical risk into programmatic language, a trait the founders need in a company selling to government buyers.

Where the Work Happens

Obviant operates from two primary locations that reflect its dual focus on proximity to defense decision-makers and access to a broader engineering talent pool. Headquarters sits in Arlington, Virginia, deliberately positioned inside the Beltway where program offices, acquisition executives, and the Pentagon's bureaucracy are within commuting distance. A second engineering hub has formed in Tampa, Florida, where the company has posted multiple senior roles including a Senior Fullstack Software Engineer and a Senior Engineering Manager on the Zero G Talent board.

The Arlington office hosts the roles that require daily fluency in DoD acquisition language: Analyst - Defense Acquisition, Senior Data & BI Automation Analyst, Senior Product Manager, a second Senior Engineering Manager, another Senior Fullstack Software Engineer, and an Account Executive, Commercial. All eight of the company's current board-listed openings are split between these two cities, with six in Arlington and two in Tampa. The board's salary bands reflect the market difference: Arlington-based Senior Fullstack Engineers are listed at $170K–$215K, while the Tampa counterpart sits at $150K–$200K; the Senior Product Manager role in Arlington carries a $180K–$220K band. These figures align with that same benchmark.

Physical workspace details are sparse in public records; the company describes itself as a "small, focused team" of approximately seven employees as of the latest executive directory data, and the founders have not published office tours or facility specs. What the research does confirm is the nature of the work that shapes those spaces. Obviant's platform ingests thousands of structured and unstructured sources: program documents, defense budget justification books, Congressional reports, and customers' proprietary data. The engineering workload centers on data pipeline reliability, large-language-model integration for reasoning over acquisition text, and secure multi-tenant infrastructure that meets government compliance thresholds.

The company's $7.1 million seed round, led by Shield Capital with participation from Motivate Venture Capital, A*, New Vista Capital, Aloft Venture Capital, and Underdog Labs, was explicitly earmarked to "expand its team, advance the AI capabilities of its platform, and broaden its customer base." That capital infusion, announced in June 2025, supports the current hiring push across both sites. The DIU prototype Other Transaction award (November 2025) and the subsequent contract expansion with the Under Secretary of War for Acquisition and Sustainment (February 2026) further signaled that the Arlington location needed to accommodate government liaison work, demo environments for program-office stakeholders, and the compliance overhead that comes with production DoD deployments.

Flexible work arrangements appear in the company's public messaging: "flexible schedule - We all have other things going on in our lives. Doctor visits, kids' activities, dog walks - take care of it whenever you have to. And work from home when you need to." The two-city footprint makes hybrid or remote options operationally necessary. The board's posting data shows no location-tagged "remote" roles, but the split itself functions as a de facto distributed model.

Obviant's physical footprint will stay lean. The mission — synthesizing thousands of DoD data sources into a single decision platform, is compute-heavy and people-light by design.

Who Thrives Here

Obviant's founding team has been explicit about the culture they're building. The careers page states it plainly: "We're a driven team with a big vision and a strong sense of purpose. If this resonates, we'd love get to know you. We're looking for others who are like-minded and ambitious to join us on the journey." That language (purpose, resonance, like-minded) isn't branding fluff. It maps directly to the problem space: making sense of the Defense Department's fragmented acquisition data so companies, investors, and government offices can act faster.

The operating culture, as described in public write-ups, favors empowerment over micromanagement, prizes perseverance on hard problems, and expects a high tempo of shipping: "move fast, ship often" is how the company describes it. Obviant looks for people who can translate user problems into effective technology and who care about government service. That last part matters. The platform serves defense companies, investors, researchers, and government offices, including program officials who use it to see the Pentagon's sprawling collection of programs and budgets more clearly. Karp told Business Insider the team spent about a year on "heads-down data scripting" to compile thousands of sources into one database, figuring out what trusted sources mattered, how to collect data from them, and how to piece them together for better understanding. That grind (unglamorous, essential, iterative) is the actual work.

The stated values reinforce the profile. "Our work matters. We take a lot of pride in building to advance mission outcomes." "We get stuff done, no matter what it takes." "Our users' problems are our own. We don't push products, we solve problems." "We're not afraid to admit what we don't know. Our job is to listen and grow." "Transparency & respect above all else. It's non-negotiable, even when it isn't easy." Read those together and a pattern emerges: low ego, high agency, mission alignment, and a tolerance for ambiguity in a domain where the data is messy and the stakes are national security.

Technically, the stack (Python, TypeScript, React, Node.js, PostgreSQL, Terraform, AWS) demands full-stack fluency, but the roles on the board show the range across engineering, product, analytics, and commercial functions as detailed in Section 1. The Arlington cluster reflects proximity to the Pentagon and the defense acquisition ecosystem; the Tampa presence signals a second hub for engineering execution. Both expect in-office collaboration most days: the founding team is in the office most days and leaves flexibility to each member, but believes being together matters.

What separates people who stay from those who churn? Three traits. First, domain curiosity: you don't need a defense background on day one, but you need to want to understand how RDT&E funding flows, what "Scaled Hypersonics" as a critical technology area means for procurement, and why a program office cares about congressional hearing citations. Second, comfort with opacity: the raw data lives across "an overwhelming number of documents, websites, organizations, and budgets," as former DIU director Michael Brown put it. Turning that into a single source of truth requires judgment calls on sourcing, schema, and freshness, not just code. Third, a builder's bias toward shipping. The platform answers questions like "where is the funding for counter-drone systems going?" or "what are the latest updates on Golden Dome?" with sourced answers, project links, news coverage, and official comments. That only happens if engineers, analysts, and product managers push complete, verifiable features at pace.

The founding duo has raised from investors including Shield Capital (where Brown is now a partner) and assembled advisors from national security and technology. The board's salary band runs roughly $154k–$219k (median $215k) across three salaried roles, with equity, health, dental, and 401(k). But the compensation is table stakes. The filter is whether the mission "equip all sides of the market with the tools they need to execute effectively, with one goal: delivering better capability to the end-user." Because mission matters above all else" — actually drives your decisions when the data pipeline breaks on a Friday and the user is a program office preparing for a Monday brief. The firehose of paperwork from the first paragraph doesn't sort itself. The people who thrive here are the ones who reach into it anyway.

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