Forward Deployed Engineer
Higharc · Austin, TX · 1 mo ago
RemoteRemoteEngineering$175/hrFull-time
We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes "About Us" (but not needed as heading). It includes "What You'll Do" (responsibilities). It includes "About You" (requirements/qualifications/skills). It includes "Working at Higharc" with remote work and travel, compensation and benefits. There's no explicit Pay or Schedule specifics; compensation mentions competitive salaries with equity, benefits, but no specific numbers. The rule: never create Pay/Schedule/Benefits sections unless posting actually states them. It does state benefits (medical, dental, vision, PTO, maternity/paternity leave, disability, 401K, stipend). So we can include Benefits section. Pay: they mention competitive salaries with significant equity, but no specific numbers; is that considered stating? It says "competitive salaries with significant equity". That is a statement about pay, albeit vague. The rule: never emit a heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD"). "competitive salaries with significant equity" is not filler? It's somewhat vague but still a statement. Might be acceptable. However they said "Prefer a few substantive sections over many thin ones." Could combine Pay and Benefits? But they want separate headings if content exists. We'll include Pay section with that sentence. Schedule: they mention travel up to 30% of time, remote work, regular team meet-ups. That's schedule info (travel expectation). So we can include Schedule section with that.
We must not repeat job title as heading. No Job ID. Remove boilerplate like cookie/navigation/legal/EEO etc. There's a fraud warning at end; that's boilerplate? It's about fraudulent recruiting activity; likely should be removed as it's not substantive. Also "Please note: we are seeing an uptick..." is boilerplate; remove.
We need to use for section headings. Use
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We need to preserve all substantive information. Let's extract.
About Us: not needed as heading but could be included as a short paragraph? The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it." About Us is not a heading we need; we could include as a paragraph before sections? The instruction says output only HTML fragment; we can include a
for About Us? It's not a section heading but could be considered part of description. However they said "Use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." So we should only use those headings if we have content. About Us is not in that list, so we should not create a heading for it. We could fold it into a short
maybe under a generic intro? But they said "fold minor metadata into a short
or drop it." About Us is not minor metadata; it's substantive about company. Might be okay to include as a
before sections without a heading. The instruction didn't forbid extra paragraphs. It just said use those headings for sections. So we can include a leading
with About Us.
Now responsibilities: "What You'll Do" bullet points. We'll make
Responsibilities
then - each bullet.
Let's list responsibilities:
- Embed with HQ, regional, and division teams to run technical discovery — profile plan assets, assess data quality, and reverse-engineer how each division's drawing sets encode variation
- Build and ship the searchable plan library, analytics dashboard, and agent-enabled natural-language search — own the pipeline from raw plan ingestion through structured, queryable output
- Tune and extend Higharc's Autotranslate AI capabilities to identify, categorize, and translate floorplans into data
- Work hands-on with the data — write the ETL, build against internal APIs, and ship working capability back to users directly rather than handing off a spec
- Build geometric similarity scoring and classification models that surface plans which have forked under different names
- Meet delivery milestones — coverage targets, data-field completeness, QA error thresholds — and flag tradeoffs in real time when schedule pressure argues against them
- Instrument and quantify results: redundancy across a catalog, dimensional spread on repeated conditions, consolidation candidates, and the purchasing leverage each one represents
- Partner with the Forward Deployed Product Manager, Technical Lead, QA, Intake Specialists, and Client Strategy, and present technical progress and tradeoffs to executive stakeholders
- Build the repeatable version — turn one-off scripts and data patterns into reusable tooling that lets the forward deployed model work on the next engagement, not just the current one
- Travel to client sites and company events up to 30% of the time.
Now About You: requirements/qualifications/skills. We'll split maybe into Requirements (experience), Qualifications (education? none), Skills (specific). But we can combine into Requirements and Skills sections.
Let's extract:
- 5+ years of engineering experience, including significant time in customer-facing or deployed settings — forward deployed engineering, solutions engineering, technical consulting, or professional services
- Strong hands-on data fluency: SQL, scripting against APIs, comfort in notebooks, and a habit of interrogating a data set yourself rather than requesting a pull
- Experience prototyping to validate ideas quickly using tools like Cursor, Replit, or V0.dev
- A track record building structured data models, taxonomies, or classification schemes and getting a system to actually run on them in production
- Strong judgment about data quality — what level of accuracy a decision requires, and what it costs to get there
- Excellent written and verbal communication, including with executive stakeholders who have limited time and no patience for status without substance
- Willingness to travel to client sites and company events up to 30% of the time
Major plus if you also bring:
- Background in residential construction, homebuilding, architecture, or AEC technology — especially fluency with plan sets, elevations, options, and how builders manage plan variation
- Experience with agent-based or natural-language search over structured data, RAG systems, or LLM-powered analytics
- Exposure to geometric or spatial data — CAD/BIM, computer vision on drawings, similarity and clustering methods
- Experience working with large, messy, enterprise-scale data migrations or ingestion programs
- Having built a function from zero: first hire into a new team, new practice, or new delivery model
We could put the core requirements in a Requirements section, and the "major plus" in Skills or Qualifications. But we can also have a Skills section for technical skills.
Let's decide: Requirements: years experience, data fluency, prototyping, track record, judgment, communication, willingness to travel. Skills: SQL, scripting, APIs, notebooks, Cursor/Replit/V0.dev, data modeling, taxonomies, classification, data quality judgment, communication, plus the major plus items.
But we need to avoid duplication. Let's create:
Requirements
- 5+ years of engineering experience, including significant time in customer-facing or deployed settings (forward deployed engineering, solutions engineering, technical consulting, or professional services)
- Strong hands-on data fluency: SQL, scripting against APIs, comfort in notebooks, and a habit of interrogating a data set yourself rather than requesting a pull
- Experience prototyping to validate ideas quickly using tools like Cursor, Replit, or V0.dev
- A track record building structured data models, taxonomies, or classification schemes and getting a system to actually run on them in production
- Strong judgment about data quality — what level of accuracy a decision requires, and what it costs to get there
- Excellent written and verbal communication, including with executive stakeholders who have limited time and no patience for status without substance
- Willingness to travel to client sites and company events up to 30% of the time
Skills
- Background in residential construction, homebuilding, architecture, or AEC technology — especially fluency with plan sets, elevations, options, and how builders manage plan variation (major plus)
- Experience with agent-based or natural-language search over structured data, RAG systems, or LLM-powered analytics (major plus)
- Exposure to geometric or spatial data — CAD/BIM, computer vision on drawings, similarity and clustering methods (major plus)
- Experience working with large, messy, enterprise-scale data migrations or ingestion programs (major plus)
- Having built a function from zero: first hire into a new team, new practice, or new delivery model (major plus)
But we might also include SQL etc under Skills; but they are already in Requirements. Could move them to Skills. However the instruction: "Prefer a few substantive sections over many thin ones." Might be better to combine Requirements and Skills into one section? But they ask to use those headings if content exists. We'll keep both.
Now Benefits: from "Working at Higharc": Remote work and travel: Our company is entirely remote, and has been since we were founded in 2018. Remote work means more time with family, less time commuting, and the flexibility to blend work and life. We value in-person collaboration and asynchronous deep-work time, which is why we schedule regular team meet-ups in our hubs across the US and, depending on the role, prioritize hiring in those hubs. If your role requires frequent travel beyond pre-scheduled team meet ups, we will represent that to the best of our ability as early as possible in the interview process. Compensation and benefits: Higharc offers competitive salaries with significant equity, in a fast-growing, well-funded company. We provide comprehensive medical, dental, and vision coverage, with flexible PTO, and meaningful maternity/paternity leave to all U.S based employees that are full-time. You'll also have access to other big-company benefits such like short and long-term disability plans and a 401K. We also provide a stipend to create the ideal home office and support ongoing L&D.
We need Benefits section: list benefits.
We'll create Benefits
- Fully remote work (since 2018) with flexibility to blend work and life
- Regular in-person team meet-ups in US hubs
- Competitive salary with significant equity
- Comprehensive medical, dental, and vision coverage
- Flexible PTO
- Meaningful maternity/paternity leave (U.S. full-time employees)
- Short and long-term disability plans
- 401(k) plan
- Home office stipend
- Ongoing learning and development (L&D) support
Pay: we could include competitive salaries with significant equity. But we already have that in Benefits. To avoid duplication, maybe we put Pay section just with that sentence, and Benefits separate. However the instruction: "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state compensation and benefits. So we can have Pay and Benefits separate.
Pay: "competitive salaries with significant equity". That's it.
Schedule: travel up to 30% of time, remote work, regular team meet-ups. We'll put in Schedule.
But we already have remote work and travel in Benefits; maybe we should keep travel in Schedule and remote work in Benefits. Let's separate.
Schedule section: "Travel to client sites and company events up to 30% of the time." Also maybe "Regular team meet-ups
for prose. We need to preserve all substantive information. Let's extract. About Us: not needed as heading but could be included as a short paragraph? The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it." About Us is not a heading we need; we could include as a paragraph before sections? The instruction says output only HTML fragment; we can include a
for About Us? It's not a section heading but could be considered part of description. However they said "Use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." So we should only use those headings if we have content. About Us is not in that list, so we should not create a heading for it. We could fold it into a short
maybe under a generic intro? But they said "fold minor metadata into a short
or drop it." About Us is not minor metadata; it's substantive about company. Might be okay to include as a
before sections without a heading. The instruction didn't forbid extra paragraphs. It just said use those headings for sections. So we can include a leading
with About Us. Now responsibilities: "What You'll Do" bullet points. We'll make
Responsibilities
then- each bullet.
Let's list responsibilities:
- Embed with HQ, regional, and division teams to run technical discovery — profile plan assets, assess data quality, and reverse-engineer how each division's drawing sets encode variation
- Build and ship the searchable plan library, analytics dashboard, and agent-enabled natural-language search — own the pipeline from raw plan ingestion through structured, queryable output
- Tune and extend Higharc's Autotranslate AI capabilities to identify, categorize, and translate floorplans into data
- Work hands-on with the data — write the ETL, build against internal APIs, and ship working capability back to users directly rather than handing off a spec
- Build geometric similarity scoring and classification models that surface plans which have forked under different names
- Meet delivery milestones — coverage targets, data-field completeness, QA error thresholds — and flag tradeoffs in real time when schedule pressure argues against them
- Instrument and quantify results: redundancy across a catalog, dimensional spread on repeated conditions, consolidation candidates, and the purchasing leverage each one represents
- Partner with the Forward Deployed Product Manager, Technical Lead, QA, Intake Specialists, and Client Strategy, and present technical progress and tradeoffs to executive stakeholders
- Build the repeatable version — turn one-off scripts and data patterns into reusable tooling that lets the forward deployed model work on the next engagement, not just the current one
- Travel to client sites and company events up to 30% of the time.
Now About You: requirements/qualifications/skills. We'll split maybe into Requirements (experience), Qualifications (education? none), Skills (specific). But we can combine into Requirements and Skills sections.
Let's extract:
- 5+ years of engineering experience, including significant time in customer-facing or deployed settings — forward deployed engineering, solutions engineering, technical consulting, or professional services
- Strong hands-on data fluency: SQL, scripting against APIs, comfort in notebooks, and a habit of interrogating a data set yourself rather than requesting a pull
- Experience prototyping to validate ideas quickly using tools like Cursor, Replit, or V0.dev
- A track record building structured data models, taxonomies, or classification schemes and getting a system to actually run on them in production
- Strong judgment about data quality — what level of accuracy a decision requires, and what it costs to get there
- Excellent written and verbal communication, including with executive stakeholders who have limited time and no patience for status without substance
- Willingness to travel to client sites and company events up to 30% of the time
Major plus if you also bring:
- Background in residential construction, homebuilding, architecture, or AEC technology — especially fluency with plan sets, elevations, options, and how builders manage plan variation
- Experience with agent-based or natural-language search over structured data, RAG systems, or LLM-powered analytics
- Exposure to geometric or spatial data — CAD/BIM, computer vision on drawings, similarity and clustering methods
- Experience working with large, messy, enterprise-scale data migrations or ingestion programs
- Having built a function from zero: first hire into a new team, new practice, or new delivery model
We could put the core requirements in a Requirements section, and the "major plus" in Skills or Qualifications. But we can also have a Skills section for technical skills.
Let's decide: Requirements: years experience, data fluency, prototyping, track record, judgment, communication, willingness to travel. Skills: SQL, scripting, APIs, notebooks, Cursor/Replit/V0.dev, data modeling, taxonomies, classification, data quality judgment, communication, plus the major plus items.
But we need to avoid duplication. Let's create:
Requirements
- 5+ years of engineering experience, including significant time in customer-facing or deployed settings (forward deployed engineering, solutions engineering, technical consulting, or professional services)
- Strong hands-on data fluency: SQL, scripting against APIs, comfort in notebooks, and a habit of interrogating a data set yourself rather than requesting a pull
- Experience prototyping to validate ideas quickly using tools like Cursor, Replit, or V0.dev
- A track record building structured data models, taxonomies, or classification schemes and getting a system to actually run on them in production
- Strong judgment about data quality — what level of accuracy a decision requires, and what it costs to get there
- Excellent written and verbal communication, including with executive stakeholders who have limited time and no patience for status without substance
- Willingness to travel to client sites and company events up to 30% of the time
Skills
- Background in residential construction, homebuilding, architecture, or AEC technology — especially fluency with plan sets, elevations, options, and how builders manage plan variation (major plus)
- Experience with agent-based or natural-language search over structured data, RAG systems, or LLM-powered analytics (major plus)
- Exposure to geometric or spatial data — CAD/BIM, computer vision on drawings, similarity and clustering methods (major plus)
- Experience working with large, messy, enterprise-scale data migrations or ingestion programs (major plus)
- Having built a function from zero: first hire into a new team, new practice, or new delivery model (major plus)
Benefits
- Fully remote work (since 2018) with flexibility to blend work and life
- Regular in-person team meet-ups in US hubs
- Competitive salary with significant equity
- Comprehensive medical, dental, and vision coverage
- Flexible PTO
- Meaningful maternity/paternity leave (U.S. full-time employees)
- Short and long-term disability plans
- 401(k) plan
- Home office stipend
- Ongoing learning and development (L&D) support